Stochastic modelling of groundwater flow and solute transport in aquifers

This paper presents an introductory overview of recently developed stochastic theories for tackling spatial variability problems in predicting groundwater flow and solute transport. Advantages and limitations of the theories are discussed. Lastly, strategies based on the stochastic approaches to predict solute transport in aquifers are recommended.     

Spatial measurements of stream baseflow,a relevant method for aquifer characterization and permeability evaluation. Application to a hard‐rock aquifer,the Oman ophiolite

The structure, functioning and hydrodynamic properties of aquifers can be determined from an analysis of the spatial variability of baseflow in the streams with which they are associated. Such analyses are based on simple low‐cost measurements. Through interpreting the hydrological profiles (Q = f(A)) it is possible to locate the aquifer(s) linked to the stream network and to determine the type of interrelated flow, i.e. whether the stream drains or feeds the aquifer. Using an analytical solution developed for situations with a positive linear relationship, i.e. where the baseflow increases linearly with increasing catchment size, it is also possible to estimate the permeability of the aquifer(s) concerned at catchment scale. Applied to the hard‐rock aquifers of the Oman ophiolite, this method shows that the ‘gabbro’ aquifer is more permeable than the ‘peridotite’ aquifer. As a consequence the streams drain the peridotites and ‘leak’ into the gabbro. The hydrological profiles within the peridotite are linear and positive, and indicate homogeneity in the hydrodynamic properties of these formations at the kilometre scale. The permeability of the peridotite is estimated at 5 · 10^?7 to 5 · 10^?8 m/s. Copyright © 2004 John Wiley & Sons, Ltd.     

Dust supply from river floodplains: the case of the lower Huang He (Yellow River) recorded in a loess–palaeosol sequence from the Mangshan Plateau

The Mangshan Plateau is located on the south bank of the Huang He (Yellow River) just west of the city of Zhengzhou, well outside the Loess Plateau in central China. Mixing models of the grain‐size data indicate that the loess deposits are mixtures of three loess components. Comparison of the mixing model with existing models established for a series of loess–palaeosol sequences from the Loess Plateau indicates that the Mangshan loess has been supplied from a proximal dust source, the Huang He floodplain, during major dust outbreaks. The high accumulation rates, the composition of the loess components, and especially the high proportions of a sandy loess component support this. Owing to the exceptionally high accumulation rates, the Mangshan grain size, magnetic susceptibility and carbonate records provide a high‐resolution archive of environmental and climate change. Copyright © 2008 John Wiley & Sons, Ltd.     

Application of micropolar plasticity to post failure analysis in geomechanics

A micropolar elastoplastic model for soils is formulated and a series of finite element analyses are employed to demonstrate the use of a micropolar continuum in overcoming the numerical difficulties encountered in application of finite element method in standard Cauchy–Boltzmann continuum. Three examples of failure analysis involving a deep excavation, shallow foundation, and a retaining wall are presented. In all these cases, it is observed that the length scale introduced in the polar continuum regularizes the incremental boundary value problem and allows the numerical simulation to be continued until a clear collapse mechanism is achieved. The issue of grain size effect is also discussed. Copyright © 2004 John Wiley & Sons, Ltd.     

Size and shape evolution of pores in a viscoplastic matrix under compression

The frequent use of soils and earth materials for hydraulic capping and for geo‐environmental waste containment motivated our interest in detailed modelling of changes in size and shape of macro‐pores to establish links between soil mechanical behaviour and concurrent changes in hydraulic and transport properties. The objective of this study was to use finite element analysis (FEA) to test and extend previous analytical solutions proposed by the authors describing deformation of a single macro‐pore embedded in linear viscoplastic soil material subjected to anisotropic remote stress. The FEA enables to consider more complex pore geometries and provides a detailed picture of matrix yield behaviour to explain shortcomings of approximate analytical solutions. Finite element and analytical calculations agreed very well for linear viscous as well as for viscoplastic materials, only limited for the case of isotropic remote stress due to the simplifications of the analytical model related to patterns and onset of matrix‐yielding behaviour. FEA calculations were compared with experimental data obtained from a compaction experiment in which pore deformation within a uniform modelling clay sample was monitored using CAT scanning. FEA predictions based on independently measured material properties and initial pore geometry provided an excellent match with experimentally determined evolution of pore size and shape hence lending credence to the potential use of FEA for more complex pore geometries and eventually connect macro‐pore deformation with hydraulic properties. Copyright © 2006 John Wiley & Sons, Ltd.     

Identification of physical processes inherent in artificial neural network rainfall runoff models

The emergence of artificial neural network (ANN) technology has provided many promising results in the field of hydrology and water resources simulation. However, one of the major criticisms of ANN hydrologic models is that they do not consider/explain the underlying physical processes in a watershed, resulting in them being labelled as black‐box models. This paper discusses a research study conducted in order to examine whether or not the physical processes in a watershed are inherent in a trained ANN rainfall‐runoff model. The investigation is based on analysing definite statistical measures of strength of relationship between the disintegrated hidden neuron responses of an ANN model and its input variables, as well as various deterministic components of a conceptual rainfall‐runoff model. The approach is illustrated by presenting a case study for the Kentucky River watershed. The results suggest that the distributed structure of the ANN is able to capture certain physical behaviour of the rainfall‐runoff process. The results demonstrate that the hidden neurons in the ANN rainfall‐runoff model approximate various components of the hydrologic system, such as infiltration, base flow, and delayed and quick surface flow, etc., and represent the rising limb and different portions of the falling limb of a flow hydrograph. Copyright © 2004 John Wiley & Sons, Ltd.     

Simulating methane emission from a Chinese rice field as influenced by fertilizer and water level

Natural and agricultural wetlands are considered to be the major sources of global atmospheric methane (CH₄). A one‐dimensional model was developed to simulate methane emission and used to examine the influence of various physical processes on the rate of methane emission. Three processes involved in the methane emission are implemented in the model: production, reoxidation and transport. Three transport pathways were considered: diffusion across water–air or soil–air interfaces, ebullition and diffusion through plants. These pathways are influenced by soil properties, plant growth, water‐table conditions, temperature and external inputs (e.g. fertilizer). The model was used to examine the seasonal variation of the methane emission at a rice field in Hunan, China, which was observed during a field experiment for consecutive (early and late) rice seasons in 1992. The observed seasonal variations of methane emission, and role of plants in transporting methane to the atmosphere, are captured by the model simulation. Further model applications were conducted to simulate effects of fertilizer and water‐level condition on the methane emission. The results indicate that unfermented organic fertilizer produces a higher methane emission rate than mineral fertilizer. The simulations with treatments of a deep‐water covering and constant moisture reduced the methane emission. The rice field study provides a framework for further development of the model towards simulations based on spatially distributed variables (e.g. water table, soil temperature and vegetation) at a regional scale. Copyright © 2003 John Wiley & Sons, Ltd.     

Ice‐cover variability on shallow lakes at high latitudes: model simulations and observations

A one‐dimensional thermodynamic model for simulating lake‐ice phenology is presented and evaluated. The model can be driven with observed daily or hourly atmospheric forcing of air temperature, relative humidity, wind speed, cloud amount and snowfall. In addition to computing the energy balance components, key model output includes the temperature profile at an arbitrary number of levels within the ice/snow (or the water temperature if there is no ice) and ice thickness (clear ice and snow‐ice) on a daily basis, as well as freeze‐up and break‐up dates. The lake‐ice model is used to simulate ice‐growth processes on shallow lakes in arctic, sub‐arctic, and high‐boreal forest environments. Model output is compared with field and remote sensing observations gathered over several ice seasons. Simulated ice thickness, including snow‐ice formation, compares favourably with field measurements. Ice‐on and ice‐off dates are also well simulated when compared with field and satellite observations, with a mean absolute difference of 2 days. Model simulations and observations illustrate the key role that snow cover plays on the seasonal evolution of ice thickness and the timing of spring break‐up. It is also shown that lake morphometry, depth in particular, is a determinant of ice‐off dates for shallow lakes at high latitudes. Copyright © 2003 John Wiley & Sons, Ltd.     

A micromechanical finite element model for linear and damage‐coupled viscoelastic behaviour of asphalt mixture

This study presents a finite element (FE) micromechanical modelling approach for the simulation of linear and damage‐coupled viscoelastic behaviour of asphalt mixture. Asphalt mixture is a composite material of graded aggregates bound with mastic (asphalt and fine aggregates). The microstructural model of asphalt mixture incorporates an equivalent lattice network structure whereby intergranular load transfer is simulated through an effective asphalt mastic zone. The finite element model integrates the ABAQUS user material subroutine with continuum elements for the effective asphalt mastic and rigid body elements for each aggregate. A unified approach is proposed using Schapery non‐linear viscoelastic model for the rate‐independent and rate‐dependent damage behaviour. A finite element incremental algorithm with a recursive relationship for three‐dimensional (3D) linear and damage‐coupled viscoelastic behaviour is developed. This algorithm is used in a 3D user‐defined material model for the asphalt mastic to predict global linear and damage‐coupled viscoelastic behaviour of asphalt mixture. For linear viscoelastic study, the creep stiffnesses of mastic and asphalt mixture at different temperatures are measured in laboratory. A regression‐fitting method is employed to calibrate generalized Maxwell models with Prony series and generate master stiffness curves for mastic and asphalt mixture. A computational model is developed with image analysis of sectioned surface of a test specimen. The viscoelastic prediction of mixture creep stiffness with the calibrated mastic material parameters is compared with mixture master stiffness curve over a reduced time period. In regard to damage‐coupled viscoelastic behaviour, cyclic loading responses of linear and rate‐independent damage‐coupled viscoelastic materials are compared. Effects of particular microstructure parameters on the rate‐independent damage‐coupled viscoelastic behaviour are also investigated with finite element simulations of asphalt numerical samples. Further study describes loading rate effects on the asphalt viscoelastic properties and rate‐dependent damage behaviour. Copyright © 2006 John Wiley & Sons, Ltd.     

The Ectoparasitic Gastropod Boonea (= Odostomia) impressa: Population Ecology and the Influence of Parasitism on Oyster Growth Rates

Abstract. Boonea (= Odostomia) impressa is a common ectoparasite of oysters. In the laboratory, small oysters (Crassostrea virginica) parasitized by natural densities of B. impressa produced 75 % less new shell than unparasitized oysters. Shell deposition rates of previously parasitized oysters increased significantly after all B. impressa were removed. Thus, the decrease in growth rate, although significant, apparently was not permanent. B. impressa preferentially parasitized small, living oysters (≤2.5cm) in the field, even though a higher percentage of large, living oysters (>2.5cm) was available. The snails maintained an aggregated distribution on the oyster reef. The number of B. impressa per oyster clump was positively correlated with the number of living oysters per clump, however some clumps with few or no living oysters had many B. impressa. Thus, food availability only partially explained the pattern of distribution. B. impressa was very mobile. About 50 % of the population moved in one week. Reproduction occurred throughout the year with a peak period in May. Recruitment was greatest in July, however new recruits were observed throughout the year. The reduction in growth rate of parasitized oysters, the snaiľs propensity towards parasitizing small oysters and the snail's tendency to be contagiously distributed suggests that B. impressa potentially exerts a significant influence on the population structure and health of oyster populations.