Subsurface fluids may travel along paths having a minimum permeabilility greater than the effective permeability of the rock. This may have an important impact on contaminant migration. A stochastic approach related to percolation theory is advanced to address the question of what is the probability that a high permeability path extends across a given volume of the subsurface. The answer is sought numerically through subdividing the volume of interest into a three-dimensional grid of elements and assigning a random permeability to each element. Four permeability processes are considered: 1) Stationary with independence between grid elements; 2) Stationary and autocorrelated; 3) Nonstationary due to conditioning on measured values; and 4) Random rock volume included in grid. The results utilizing data from fractured granites suggest that in large grids, at least one path having a minimum permeability in excess of the "effective" rock permeability will cross the grid. Inclusion of autocorrelation causes an increase in the expected value of the minimum permeability of such a path. It also results in a significantly increased variance of this permeability. Conditioning on field permeabilities reduces the variance of this value over that obtained by unconditional, correlated simulation, but still produces a variance greater than that obtained when independence was assumed. When conditioning is performed, the mean of the minimum permeabilities along these paths is dependent on the principal axis of the path. Finally, including a random rock volume by allowing the length of the grid to be random increases the variance of the minimum permeability.

A hydrological modelling effort using MODFLOW was undertaken in order to determine the relative importance of some of the factors influencing hydraulic gradient reversals in peatlands. Model domains were of two types, large raised bog type (LRBT) and kettle bog type (KBT), and were made to undergo various levels of meteorological forcing (water deficit). Substrate, too, was varied in order to determine its importance on reversals. Domain-wide reversals were successfully simulated in LRBT systems, but not in KBT systems. Although simulated flow patterns matched field-observed patterns, both pre- and post-drought, simulated reversals occurred more quickly than in the field. This may be due to insufficiently distributed parameters, such as hydraulic conductivity. Reversals were easily terminated by simulating non-drought conditions. In the LRBT system, reversal duration decreased, and time-to-reversal increased, with a decrease in drought severity. Increasing drought severity in KBT systems had the opposite effect on the duration of semi-reversed flow patterns, suggesting a possibly different/additional mechanism for flow reversals in KBT systems. Hydraulic conductivity had an appreciable effect on flow reversal evolution, though neither changing porosity, nor differences in catotelm layering had a great effect.

No description available.

Water is characterised by both its quantity (availability) and its quality. Salinity, which is one of the major water quality parameters limiting use of a wide range of land and water resources, refers to the total dissolved solutes in water. It is influenced by a combination of several soil-water-salt-plant related processes. In order to develop optimum management schemes for environmental control through relevant hydrological modelling techniques, it is important to identify and understand these processes affecting salinity. Therefore, the various sources and processes controlling salt release and transport from the soil surface through the root zone to groundwater and streams as well as reservoirs are extensively reviewed in this project with subsequent exploration of some hydro salinity modelling approaches. The simulation of large and complex hydrological systems, such as these at a catchment scale, requires a flexible and efficient modelling tool to assist in the assessment of the impact of land and water use alternatives on the salt balance. The currently available catchment models offer varying degrees of suitability with respect to modelling hydrological problems, dependent on the model structure and the type of the approach used. The A CR U agrohydrological modelling system, with its physically-conceptually based characteristics as well as being a multi-purpose model that is able to operate both as a lumped and distributed model, was found to be suitable for hydro salinity modelling at a catchment scale through the incorporation of an appropriate hydro salinity module. The main aim of this project was to develop, validate and verify a hydro salinity module for the ACRU model. This module is developed in the object-oriented version of ACRU, viz. ACRU2000, and it inherits the basic structure and objects of the model. The module involves the interaction of the hydrological processes represented in ACRU and salinity related processes. Hence, it is designated as ACRUSalinity. In general, the module is developed through extensive review of ACRU and hydrosalinity models, followed by conceptualisation and design of objects in the module. It is then written in Java object-oriented programming language. The development of ACRUSalinity is based mainly on the interaction between three objects, viz. Components, Data and Processes. Component objects in ACRU2000 represent the physical features in the hydrological system being modelled. Data objects are mainly used to store data or information. The Process objects describe processes that can take place in a conceptual or real world hydrological system. The Process objects in ACRUSalinity are grouped into six packages that conduct: • the initial salt load determination in subsurface components and a reservoir • determination of wet atmospheric deposition and salt input from irrigation water • subsurface salt balance, salt generation and salt movement • surface flow salt balance and salt movement • reservoir salt budgeting and salt routing and • channel-reach salt balancing and, in the case of distributed hydro salinity modelling, salt transfer between sub-catchments. The second aim of the project was the validation and verification of the module. Code validation was undertaken through mass balance computations while verification of the module was through comparison of simulated streamflow salinity against observed values as recorded at gauging weir UIH005 which drains the Upper Mkomazi Catchment in KwaZuluNatal, South Africa. Results from a graphical and statistical analysis of observed and simulated values have shown that the simulated streamflow salinity values mimic the observed values remarkably well. As part of the module development and validation, sensitivity analysis of the major input parameters of ACRUSalinity was also conducted. This is then followed by a case study that demonstrates some potential applications of the module. In general, results from the module evaluation have indicated that ACRUSalinity can be used to provide a reasonable first order approximation in various hydrosalinity studies. Most of the major sources and controlling factors of salinity are accommodated in the ACRUSalinity module which was developed in this project. However, for a more accurate and a better performance of the module in diversified catchments, further research needs to be conducted to account for the impact of salt loading from certain sources and to derive the value of some input parameters to the new module. The research needs include incorporation in the module of the impact of salt loading from fertilizer applications as well as from urban and industrial effluents. Similarly, further research needs to be undertaken to facilitate the module's conducting salt routing at sub-daily time step and to account for the impact of bypass flows in heavy soils on the surface and subsurface salt balances. / Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 2003.