A5072563409- Groundwater flow and contamination studies
- Hydrology and Watershed Management Studies
- Groundwater and Isotope Geochemistry
- Reservoir Engineering and Simulation Methods
- Water resources management and optimization
- Plant Water Relations and Carbon Dynamics
- Light effects on plants
- Magnetic and Electromagnetic Effects
- Horticultural and Viticultural Research
- Irrigation Practices and Water Management
- Groundwater and Watershed Analysis
- Geophysics and Gravity Measurements
- Environmental Impact and Sustainability
- Diamond and Carbon-based Materials Research
- Advanced Multi-Objective Optimization Algorithms
- Rice Cultivation and Yield Improvement
- Atmospheric and Environmental Gas Dynamics
- Remote Sensing in Agriculture
- Sepsis Diagnosis and Treatment
- Scientific Computing and Data Management
- Semiconductor materials and devices
- Flood Risk Assessment and Management
- Radiology practices and education
- Wine Industry and Tourism
- Greenhouse Technology and Climate Control
The University of Adelaide
2020-2023
GNS Science
2016-2020
Crown Research Institutes
2019-2020
Flinders University
2013-2017
National Centre for Groundwater Research and Training
2013-2017
The degree with which to parameterize a computer model that is be used for risk-based resource management decision support has been topic of much discussion in the environmental modeling industry, and remains difficult choice facing practitioners. High-dimensional parameterization schemes allow more robust expression input uncertainty over traditional lower-dimensional schemes, but often incur higher computational burden require greater understanding inverse problem theory implement...
A fully-worked example of decision-support-scale uncertainty quantification (UQ) and data assimilation (DA) is presented. The analyses are implemented for an existing groundwater flow model the Edwards Aquifer, Texas, USA, completed in a script-based workflow that strives to be transparent reproducible. High-dimensional parameter DA used history-match simulated outputs corresponding state observations spring discharge level. Then hindcast historic drought made. Using available recorded...
An open-source tool has been developed to facilitate constrained single- and multi-objective optimization under uncertainty (CMOU) analyses. The uses the well-known PEST interface protocols communicate with underlying forward simulation, making it non-intrusive. contains a built-in parallel run manager make use of heterogeneous distributed computing resources. Several popular evolutionary algorithms are implemented can be combined range approaches represent in model-derived...
Abstract. It has been advocated that history matching numerical models to a diverse range of observation data types, particularly including environmental tracer concentrations and their interpretations derivatives (e.g., mean age), constitutes an effective appropriate means improve model forecast reliability. This study presents two regional-scale modeling case studies directly rigorously assess the value discrete tritium concentration observations tritium-derived residence time (MRT)...
Human space exploration cannot occur without reliable provision of nutritious and palatable food to sustain physical mental well-being. This ultimately will depend upon efficient production in space, with on-site manufacturing on stations or the future human colonies celestial bodies. Extraterrestrial environments are by their nature foreign, exposure various kinds plant stressors likely be avoided. But this also offers opportunities rethink as a whole. We used boundaries Earth ecosystem...
Over the next century, coastal regions are under threat from projected rising sea levels and potential emergence of groundwater at land surface (groundwater inundation). The economic social damages this largely unseen, often poorly characterised natural hazard substantial. To support risk-based decision making in response to emerging hazard, we present a Bayesian modelling framework (or workflow), which maps spatial distribution level uncertainty inundation Intergovernmental Panel on Climate...
The ability of 'digital agriculture' to support on-farm decision making is predicated on the real-time combination observations and prior knowledge into an integrated digital environment. mathematical discipline that seeks provide this integration known as model data assimilation (DA), with demonstrated benefits including improved predictive reliability, capacity identify unexpected changes in field conditions potential measurement errors. Despite routine adoption other fields, delayed DA...
Abstract One of the first and most important decisions facing practitioners when constructing a numerical groundwater model is vertical discretization. Several factors will influence this decision, such as conceptual system hydrostratigraphy, data availability, resulting computational burden, purpose modeling analysis. Using coarse discretization an attractive option for because it reduces requirements construction efforts, can increase stability, reduce demand. However, using form...
This paper presents a framework to systematically compare the contributions uncertainty in hydro-economic simulated outputs from surrounding input parameters employed by hydrologic and economic models independently. We consider an illustrative case study example. An integrated modeling is adopted, involving surface-water/groundwater nitrate-transport model, multi-regional Computable General Equilibrium model. Environmental are determined optimizing nitrate-loading under ecologically-relevant...
Abstract. It has been advocated that history-matching numerical models to a diverse range of observation data types, particularly including environmental tracer concentrations and their interpretations/derivatives (e.g., mean age), constitutes an effective appropriate means improve model forecast reliability. This study presents two regional-scale modeling case studies directly rigorously assess the value discrete tritium concentration observations tritium-derived residence time (MRT)...
The potential of digital agriculture to support on-farm decision making is predicated on the assumption that 'cause-and-effect' relationships can be encoded in a mathematical form. One particularly important application area irrigation making, which informed by relationship between applied water and end-of-season crop yield ('water production relations'). Yet this often partial, owing its many determining factors, especially for woody perennial crops such as grapevines. Process-based models...
Future long-term human exploration of space will need a supply resources for astronauts, including fresh food from farms. This means it is necessary to identify combinations crops that can be successfully grown together and which provide balanced palatable diet astronauts. We used numerical optimization such combinations, using macro- micronutritional content as constraints, while optimizing water load needed crop farming. The constraints considered were based on the recommendations National...
Abstract The estimation of recharge through groundwater model calibration is hampered by the nonuniqueness and aquifer parameter values. It has been shown recently that estimability spatially distributed steady‐state models for practical situations (i.e., real‐world, field‐scale settings) limited need excessive amounts hydraulic‐parameter groundwater‐level data. However, extent to which temporal variability can be informed transient calibration, involves larger water‐level datasets, but...
Effective decision making for resource management is often supported by combining predictive models with uncertainty analyses. This combination allows quantitative assessment of strategy effectiveness and risk. Typically, history matching undertaken to increase the reliability model forecasts. However, question whether potential benefit will be realized, or outweigh its cost, seldom asked. History adds complexity modeling effort, as information from historical system observations must...
type transform count initial value upper bound lower standard deviation coastal boundary conductance log 14 0.576089 to 5 -3 1.33333 river-bed 67 -0.767135 5.69897 1.44983 mixed 271 3.28756 500000 0.001 83333.3 drain 1 -2.28602 2 0.833333 horizontal hydraulic conductivity 235 -1.43573 4 -4 0.69897 0.333333 1.1165 horizontal-vertical anisotropy factor 187 0.897056 3 0 0.5 porosity -1 -0.823909 0.362682 (irrigation well) abstraction rate multiplier none 98.9137