Obtaining basic simulation data for a heterogeneous field with stratified marine soils

Thinly stratified sedimentary deposits in a heterogeneous field were investigated to obtain basic physical data for the simulation of water flow. A procedure is described which translates a thinly stratified soil profile into a number of functional layers using functional hydrological properties. A functional layer is defined as a combination of one or more soil horizons and should (i) be recognizable during a soil survey using an auger and (ii) show significantly different functional hydrological properties when compared with another functional layer. This procedure gave three easily recognizable functional layers. Sets of hydrological characteristics of these three functional layers were obtained by physical measurements of the soil and by estimation, using textural data for classification into a standard Dutch series. The performance of several combinations of these sets was tested by comparing simulated and measured soil matric potentials for seven plots during one year. The best simulation results were obtained if measured soil hydraulic characteristics were used for relatively homogeneous functional layers and if the soil hydraulic characteristics were estimated at each location for the most heterogeneous layer.     

Oil-weathering behavior in Arctic environments

Oil-weathering processes in ice-free subarctic and Arctic waters include spreading, evaporation, dissolution, dispersion of whole-oil droplets into the water column, photochemical oxidation, water-in-oil emulsification, microbial degradation, adsorption onto suspended particulate material, ingestion by organisms, sinking, and sedimentation. While many of these processes also are important factors in ice-covered waters, the various forms of sea ice (depending on the active state of ice growth, extent of coverage and/or decay) impart drastic, if not controlling, changes to the rates and relative importance of different oil-weathering mechanisms. Flow-through seawater wave-tank experiments in a cold room at −35°C and studies in the Chukchi Sea in late winter provide data on oil fate and effects for a variety of potential oil spill scenarios in the Arctic. Time-series chemical weathering data are presented for Prudhoe Bay crude oil released under and encapsulated in growing first-year columnar ice through spring breakup.     

Water transport from the North-east Irish Sea to western Scottish coastal waters: Further observations from time-trend matching of Sellafield radiocaesium

Radiocaesium isotopes, discharged into the North-east Irish Sea from the Sellafield (formerly Windscale) nuclear fuel reprocessing plant in Cumbria, have been employed as flow monitors to update and extend the record of coastal water movement from the Irish Sea to the Clyde Sea area and, further north, to Loch Etive. The temporal trends in radiocaesium levels have been used to determine the extent of water mixing en route and to define mean advection rates. Flow conditions from the Irish Sea have changed considerably since the mid-1970s, the residence time of northern Irish Sea waters being ～12 months during 1978–1980 inclusive. Average transport times of four and six months are estimated for the Sellafield to Clyde and Sellafield to Etive transects respectively. Sellafield ¹³⁷Cs levels in seawater were diluted by factors of 27 and 50 respectively during current movement to the Clyde and Etive areas. The decrease in salinity-corrected ¹³⁷Cs concentrations between the Clyde and Etive suggests that dilution by Atlantic water occurs, the latter mainly entering the Firth of Lorne from the west. The majority (～94%) of the radiocaesium supply to Loch Etive enters the Firth of Lorne via the portion of the coastal current circulating west of Islay, only ～6% arriving via the Sound of Jura.     

Stable nonlinear methods for sensor array processing;

Most nonlinear high-resolution bearing estimators are unstable in the presence of correlated noise, system phase errors, and multipath arrivals because they inadvertently place too much emphasis on unstable eigenvectors of the cross-sensor correlation matrix. For moderately correlated noise there will be sufficiently many stable eigenvectors to resolve and localize discrete sources. A method is given (the "stable nonlinear method" or SNLM) whereby reweighting of the eigenvectors is achieved implicitly, without actual calculation of the eigenvectors. This SNLM is compared with Capon's maximum likelihood method (MLM) in simulations of correlated noise, partially correlated signals, and phase errors, and is shown to provide good stability in the cases considered.