Rachel Blakers

A reassessment of the Lower Namoi Catchment aquifer architecture and hydraulic connectivity with reference to climate drivers

We demonstrate the need for better representations of aquifer architecture to understand hydraulic connectivity and manage groundwater allocations for the ∼140 m-thick alluvial sequences in the Lower Namoi Catchment, Australia. In the 1980s, an analysis of palynological and groundwater hydrograph data resulted in a simple three-layer stratigraphic/hydrostratigraphic representation for the aquifer system, consisting of an unconfined aquifer overlying two semi-confined aquifers. We present an analysis of 278 borehole lithological logs within the catchment and show that the stratigraphy is far more complex. The architectural features and the net-to-gross line-plot of the valley-filling sequence are best represented by a distributive fluvial system, where the avulsion frequency increases at a slower rate than the aggradation rate. We also show that an improved understanding of past climates contextualises the architectural features observable in the valley-filling sequence, and that the lithofacies distribution captures information about the impact of climate change during the Neogene and Quaternary. We demonstrate the correlation between climate and the vertical lithological succession by correlating the sediment net-to-gross ratio line-plot with the marine benthic oxygen isotope line-plot – a climate change proxy. Pollens indicate that there was a transition from a relatively wet climate in the mid–late Miocene to a drier climate in the Pleistocene, with a continuing drying trend until present. Groundwater is currently extracted from the sand and gravel belts associated with the high-energy wetter climate. However, some of these channel belts are disconnected from the modern river and flood zone. We show that the cutoff between the hydraulically well- and poorly connected portions of the valley-filling sequence matches the connectivity threshold expected from a fluvial system.

Methods for Exploring Uncertainty in Groundwater Management Predictions

Models of groundwater systems help to integrate knowledge about the natural and human system covering different spatial and temporal scales, often from multiple disciplines, in order to address a range of issues of concern to various stakeholders. A model is simply a tool to express what we think we know. Uncertainty, due to lack of knowledge or natural variability, means that there are always alternative models that may need to be considered. This chapter provides an overview of uncertainty in models and in the definition of a problem to model, highlights approaches to communicating and using predictions of uncertain outcomes and summarises commonly used methods to explore uncertainty in groundwater management predictions. It is intended to raise awareness of how alternative models and hence uncertainty can be explored in order to facilitate the integration of these techniques with groundwater management.

Modelling for Managing the Complex Issue of Catchment-Scale Surface and Groundwater Allocation

Kinetic Analysis of the Coke Calcination Processes in Rotary Kilns.- Behavior of Elastomeric Seismic Isolators Varying Rubber Material and Pad Thickness: A Numerical Insights.- Numerical Simulation of Coastal Flows in Open Multiply-connected Irregular Domains.- System Dynamics and Agent-based Simulation for Prospective Health Technology Assessments.- Simple and Efficient Algorithms to get a Finer Resolution in a Stochastic Discrete Time Agent-based Simulation.- Numerical Study of Turbulent Boundary-layer Flow Induced by a Sphere above a Flat Plate.- Airflow and Particle Deposition in a Dry Powder Inhaler: An Integrated CFD Approach.Air pollution caused by small particles is a major public health problem in many cities of the world. One of the most contaminated cities is Mexico City. The fact that it is located in a volcanic crater surrounded by mountains helps thermal inversion and imply a huge pollution problem by trapping a thick layer of smog that float over the city. Modeling air pollution is a political and administrative important issue due to the fact that the prediction of critical events should guide decision making. The need for countermeasures against such episodes requires predicting with accuracy and in advance relevant indicators of air pollution, such are particles smaller than 2.5 microns (PM 2.5). In this work two different fuzzy approaches for modeling PM 2.5 concentrations in Mexico City metropolitan area are compared with respect the simple persistence method.