Spatial metadata plays an important role in promoting spatial data sharing and re-use to support activities that require spatial data such as development planning. It contains information about geographic or spatial data descriptions that will help spatial data users to discover and select spatial from spatial data catalogue systems or geoportals. However, the usability of spatial metadata for spatial data users is questioned. On one hand, metadata is created following standards originally designed for spatial data producers for data inventory purposes with the information mostly come from the producers’ knowledge and understanding about the spatial data. On the other hand, spatial data users come from different backgrounds with different level of knowledge to spatial data that is not necessarily similar to the owners’ knowledge. The need for improving the usability of spatial metadata for spatial data users has necessitated an understanding of the interaction between data users and the metadata, as well as with the spatial data. Due to the necessities of gathering such behavioural data from actual spatial data users, in an environment they are familiar with, User-Centred Design (UCD) has been employed as an approach. Think-Aloud Protocol (TAP), interviews and surveys were implemented as empirical UCD methods for this research. At the first stage, TAP, interviews and surveys were conducted to evaluate the usability and to identify the usability problems of the existing metadata and user interface, as well as to gather users’ needs and expectations of the metadata based on their needs of spatial data. The aims are to provide the baseline or reference for usability improvement and to gather the required information for developing a user-oriented spatial metadata profile, based on the ISO 19115:2014 metadata standard. The profile was used as the basis for a synchronised metadata development approach, where it was simultaneously manifested into functional metadata and user interface design and capabilities, to be proposed as a solution for improving metadata usability. The TAP and interviews were conducted at the final stage to test and evaluate the usability of the newly developed metadata and discovery system against the baseline or reference acquired at the first stage. The findings provide a better understanding of how spatial data users employ metadata for spatial data discovery and selection, based on their activities with the spatial data. The first usability testing found that the usability of metadata is not solely determined by the information contained in the metadata records, but it is also depended on the usability and of the user interface. The results also found that information related to previous user experiences along with the live map viewer of spatial data provide a significant improvement to the effectiveness of the spatial data selection process. In the meantime, the user interface design following the user needs and requirements significantly increase the efficiency of the spatial data discovery and selection process.

Cities around the world make major investments to mitigate the impacts of urban stormwater, such as flash flooding and degradation of receiving waters. Stormwater infiltration systems are popular worldwide, particularly in suburban and peri-urban areas, given their potential to improve water quality and reduce peak flows, while at the same time recharge groundwater and stream baseflows. The benefit of this investment is, however, somewhat uncertain, because little is known about the fate of infiltrated water and associated solutes in an urban area, where the complex network of underground infrastructure and its surrounding permeable trenches provide preferential flow paths for the infiltrated water and associated solutes. The overall goal of this research is to better understand the potential for mobilization of infiltrated stormwater pollutants in urban subsurfaces, which is achieved through the following research questions: 1. What is the effect of soil clay mineralogy on the transport of reactive solutes? 2. How do gravel filled preferential flow paths affect reactive solutes transport in soils? or what is the impact of the urban karst on the transport of reactive solutes? I used a combination of laboratory experiments and modeling approach to answer the above questions. First, I investigated the reactive transport of solutes (exemplified by zinc) using single solute batch tests. I found that 2:1 clay minerals (e.g., muscovite) in natural soil significantly contribute to zinc sorption. I also found that the maximum sorption capacity of soil that contains varied clay type fractions cannot be directly predicted from individual mineral types reported in the literature. I then investigated the transport of zinc through natural soil using column tests to better mimic the natural systems. I observed that zinc was highly retarded in the natural soil due to relatively high clay content and its mineralogy including a significant fraction of muscovite. I observed a dispersed asymmetrical breakthrough of zinc with long tailings in the columns. Fitting the asymmetric breakthrough curves of zinc with the HYDRUS-1D numerical model suggested that chemical non-equilibrium sorption was dominant. The modeling results also showed that the batch sorption data cannot be directly used in a transport model when the residence time of a reactive solute in the soil is not long enough to reach equilibrium. This result reinforces the necessity of using flow-through experiments to better approximate field conditions by simulating the dynamic transport of reactive solutes through natural soils with varied clay mineralogies. Finally, I used a preferential flow cell representing urban infrastructure to examine the impact of preferential flow paths on zinc transport. I then applied HYDRUS-1D to predict the zinc breakthrough curve through the low-permeability field soil (single medium) in the larger flow cell. Comparing the modeled breakthrough curve within the homogeneous condition in the large flow cell with that experimentally observed in the preferential flow case, I found that the breakthrough of zinc was much faster and displayed a greatly different shape due to preferential flow path. While transport through the preferential column was fast, there was a significant movement of water and zinc into the low-permeability media, due to radial diffusion. Predicted radial diffusion of zinc from an approximate solution substantially overestimated the fate and transport of zinc into the low-permeability region. The results of this thesis suggest that stormwater managers should consider soil clay mineralogy and the existence of underground infrastructure when designing and locating stormwater infiltration systems so that these systems protect and restore rather than degrade – water quality of urban streams. Without such understanding, stormwater infiltration could have unintended negative consequences, including the potential to mobilize solutes from soils and groundwater into surface waters.

Riverine water quality deterioration has become a global issue, affecting freshwater and near-shore marine ecosystems. To protect aquatic environmental health in these systems, effective water quality management strategies are critically important. Riverine water quality needs to be evaluated and managed at the catchment scale. Management decisions can be greatly supported and informed by understanding of: (1) the processes influencing water quality constituent concentrations; and (2) the key factors affecting these processes and by predictive capability. As such, catchment water quality modelling tools are important to gain this knowledge and predict water quality dynamics under different climatic and land use scenarios. A key challenge in modelling stream water quality dynamics is that there is the lack of comprehensive understanding of the role and importance of the various factors that drive differences in water quality across space and time, specifically: 1) the importance of catchment characteristics on the spatial variability in water quality; and 2) the importance of variations in environmental variables including weather and vegetation cover on the temporal variability in water quality in different landscapes. These issues have jointly led to a lack of predictive power of water quality models for multiple catchments over large regions. This research aims to improve current understanding of how riverine water quality varies spatially and temporally and the factors that drive this and to develop improved data-oriented analytical and predictive frameworks to achieve this. In this research, I investigated long-term, multiple-site water quality monitoring datasets to identify the dominant factors affecting pollutant processes and thus to inform water quality management. This research focused on the Great Barrier Reef (GBR) catchments in sub-tropical and tropical north-eastern Australia. The GBR has high environmental, societal and economical values both nationally and globally. This thesis contains three results chapters to achieve the overarching research objective. Chapter 4 addresses the spatial pattern of water quality and its linkage with heterogeneity in catchment landscape characteristics, using multivariate statistical analyses. By comparing spatial differences in long-term averaged water quality and catchment landscape characteristics, two groups of catchments were identified. This grouping reflected the main differences in water quality: group one sites had lower time-averaged concentrations (except for NOX), which were situated in wet areas with high sugar cane production and conservation zones, while group two sites had relatively higher average concentrations, were drier and with considerable grazing land use. Chapter 5 reports on an investigation into the relationships between spatial variability in water quality and catchment characteristics, using a multi-model statistical modelling approach. Specifically, the aim was to identify key catchment characteristics influencing average event-mean concentrations and to develop a spatial model predicting this. Results indicated that natural catchment characteristics were important factors for determining the variation of sediments and particulate nutrients over space, while anthropogenic characteristics (i.e., land use) were more important factors for dissolved nutrients species. The models developed were able to predict average event-mean concentrations well, with Nash-Sutcliffe efficiency (NSE) ranging from 0.64 to 0.98. Chapter 6 presents an investigation into the key factors affecting temporal changes in water quality, as summarized by variations in constituent event-mean concentrations. A Bayesian hierarchical modelling coupled with a Bayesian model averaging approach was used to evaluate the temporal change in stream water quality. The modelling results demonstrated that the key temporal controls varied between the two clusters of sites identified in Chapter 4, as well as among different constituents. Overall, catchment ground cover condition and soil moisture prior to runoff events were of greatest importance in determining the temporal change in event-mean concentration and event discharge characteristics were also important. Results from the three chapters were brought together to assess the degree to which the result has the potential to support the current water quality management and inform future design of water quality management in the GBR catchments. The spatial modelling results support the current working hypotheses underpinning water quality management in the GBR catchments, that cattle grazing, and sugarcane land uses are management priorities to reduce sediment and dissolved inorganic nitrogen, respectively. Based on the temporal modelling results, the future management practices could focus on maintaining good vegetation cover, especially for large and grazed catchments before the wet season. Finally, the water quality modelling framework used in this research provides a potential tool to evaluate catchment water quality, and what can be done to improve it, under future changes to climate, land uses and land management.

Abstract Anastomosing rivers are characterised by their low stream power (<10 Wm-2) in low-gradient floodplains (slope ~ 0.02%) and fine-grained cohesive sediments with minimal lateral activity. These rivers have a significant endemic and range-restricted biodiversity and the annual flood cycle is the basis of subsistence of the local population, providing water, arable land, and wetland resources. Consequently, they play a vital role in sustaining the cultural and environmental life of their basins. However, they are under increasing pressure on land use and water demands. In order to determine a sustainable level of water allocation for human purposes, their flow regime should be characterised first. Typically, hydrological modelling is employed to estimate how changes in climate and proposed water plans might affect surface and groundwater resources. However, hydrological modelling in the large-scale, sparsely gauged, spatially complex, low-gradient arid anastomosing floodplains with high annual flow variability is challenging. In Australia, previous attempts to characterise transmission loss in the wide anastomosing floodplains (width ~ 50 km) of Lake Eyre Basin were largely based on simplistic conceptual models, incorporating only gauged streamflow or coarse grid-based semi-distributed hydrological models. Consequently, they provided a poor representation of spatial patterns for flow paths and transmission loss. In this thesis, it was hypothesised that considering the volume and spatiotemporal features of direct floodplain rainfall and ungauged runoff from catchments surrounding floodplains significantly improves the accuracy of their water balance. In addition, accurate mapping of water extent and subsequent vegetation by remote sensing data is critical to model evapotranspiration dynamics over time and space. These two hypotheses will provide a more realistic conceptualisation of transmission loss patterns in the anastomosing rivers. After the introduction (Chapter 1) and literature review (Chapter 2), in the first part of the thesis (Chapter 3), an integrated framework for characterising floodplain response dynamics of water, vegetation and moisture was developed using optical remote-sensing. Daily time series of multispectral indices derived from MODIS images were utilised in the middle reaches of the Cooper Creek floodplain, the largest catchment of the Lake Eyre Basin in Australia. Findings indicated that in the extremely flat Cooper Creek floodplain, mapping inundation area by subsequent vegetation changes using NDVI provides more accurate results than surface water mapping area and the difference in their inundation mappings mainly occurs at the border of inundated edges, where the residence time of water is likely less than a day. Whereas, water and moisture indices (mNDWI and LSWI) outperform NDVI in detecting inundation extent in large water bodies (like Yamma Yamma Lake). In addition, by studying surface water and subsequent vegetation response together, it is possible to generate new information, such as the lag time between flooding and peak vegetation growth, and persistence time of surface water and green vegetation, which provide important hydroecological time scales in the arid zone floodplain. In the second part (Chapter 4), the significance of ungauged inflow and direct floodplain rainfall on the water balance of the Cooper Creek was investigated. Results indicated that ungauged streamflow mainly impacts the outflow volume of large flood events when the monsoon rainfall of tropical origin advances further south to inland Australia. In medium-size floods, ungauged flow is significant only when the ungauged catchments near the outlet receive considerable rainfall. In addition, local storms that are not captured by the sparse rainfall gauges of the ungauged catchments can impose high uncertainty on the water balance of flood events. Then, the proportion of rainfall contributing to the routing flow was estimated by means of remotely sensed inundation extent. In small and medium events, often <10% of the rainfall volume contributes to the surface runoff, a figure that increases to 33% for very large events; when a large proportion of floodplain area is inundated. Findings demonstrated that direct floodplain rainfall can play significantly in the water balance of all flood sizes. Besides rainfall volume, other factors like the spatial and temporal pattern of rainfall impact the outflow volume in the large-scale anastomosing rivers. In the third part of the research (Chapter 5), inundation mapping results in the first part, and water balance analysis in the second part of the thesis were incorporated to estimate event-based transmissions loss patterns over time and space. Initially, water loss volume estimated by two remotely sensed evapotranspiration products (MOD16A2 and CMRSET) were compared to the loss volume given by water balance modelling. Then, the pixel-based daily evaporation depth of these products was compared to the remotely sensed land cover changes at the peak water and vegetation phases of flooding response. Findings indicated that MOD16A2 highly underestimated transmission loss volume of the Cooper Creek events and it was further abandoned. CMRSET model overestimated transmission loss volume, especially in small size floods; however, it was capable to get improved. CMRSET model was modified and spatiotemporal pattern of transmission loss for a wide range of flood events was produced. Modified results demonstrated that plant transpiration is relatively insignificant in small to medium floods comprising on average ~10% of the transmission loss. This figure increased to 30% in wet periods, when consecutive flood events occurred in short intervals, and vegetation cover received water more frequently. In addition, transmission loss ratio (the ratio of transmission loss volume to inflow volume) was higher in the medium size events than the small and large floods because flooding water was trapped in the waterholes concentrated in the middle narrow parts of the Cooper Creek and evaporation area extended above bankfull level of primary channels to large floodplains. The significance of this thesis is developing a new method to provide a gridded water loss product in anastomosing rivers, where conventional hydrological models do not provide satisfactory results. In addition, an integrated framework was invented to characterise multiple land covers dynamics induced by dryland floods. Furthermore, a new technique was devised to evaluate remotely sensed evapotranspiration products by utilising multispectral remotely sensed indices in data-poor regions. Introduced methodologies provide a comprehensive tool to characterise the hydrology of arid zone anastomosing rivers, leading to a better understanding of their ecosystem and improving their environmental management.

Negotiations among drivers and pedestrians are common on roads, but it is still challenging for a self-driving vehicle to negotiate for its right of way with other human road users, especially pedestrians. Currently, self-driving vehicles are expected to exhibit a conservative behavior by always yielding to the approaching pedestrians. This effect will slow down the future urban traffic significantly. In this thesis, a novel model of vehicle-pedestrian negotiation is proposed describing the processing and exchange of negotiation cues from both parties. The motion strategy for the vehicle approaching the pedestrian is formulated to negotiate its best chance to pass first. The research aims to reduce the conflict of interests between vehicles and pedestrians in typical traffic conditions, yet without compromising safety. This research has been investigated in various stages. First, a preliminary review on formal traffic gestures is conducted to investigate the language of traffic. Then, negotiation concepts are established to demonstrate negotiations between a single vehicle and a single pedestrian based on physical constraints between them. The negotiation model is further extended by introducing fuzzy informal social rules for negotiations between groups of vehicles and pedestrians. The social rules are further studied, along with the risk-taking behaviors of pedestrians to extend the model to allow individual decision making among multiple vehicles and pedestrians. Lastly, the scalability of the model is validated by demonstrating multi-party negotiations. The possible negotiation opportunities for vehicles are modeled considering different risk-taking behaviors of pedestrians. The model is implemented and tested in a micro-simulation traffic environment using SUMO and MATLAB. The behavior of individual vehicles and pedestrians are simulated along with an unmarked road network to test the impact on traffic flow. The simulation environments were defined to represent different complexities of traffic ranging from one-to-one vehicle-pedestrian interactions to multi-party vehicles-pedestrians’ interactions. In different traffic conditions, the simulation results show an overall improvement in the waiting time of vehicles and thus in the intersection throughput, compared to conservative vehicle behavior (up to 50% improvement in peak traffic conditions). The simulation results also show that the benefits of reduced waiting times for vehicles come at the cost of some waiting time for pedestrians. However, the observed pedestrian waiting times in this model are not longer than the generally accepted waiting times reported in empirical studies. The results however largely depend on pedestrians' behaviors and situational factors. This research captures those factors and different pedestrian behaviors while evaluating the research hypothesis. Despite, the results are subjected to a few simulation constraints, especially dealing with the uncertainty in estimation pedestrians' intentions. Yet, this thesis is able to demonstrate possible directions for innovations in future human-vehicle interactions to maintain a smoother flow of traffic. Ultimately, this research is able to demonstrate that negotiations in future can balance the right of way among vehicles and pedestrians, especially when the interaction happens at unregulated intersections. The concepts and concerns related to social behavior of self-driving vehicles presented in this research, along with the implications of this particular research, can further help in the future to improve the decision making of self-driving vehicles when they will be sharing the roads with humans.

Disaster response is the most crucial phase in the cycle of disaster management. With increased information, disaster management stakeholders are possible to reduce community harm and save lives. Currently, the spatial information used in the response phase is collected from two sources, authoritative channels and Volunteered Geographic Information. Although the authoritative information is more reliable, it might be outdated or limitedly available during the response. By contrast, Volunteered Geographic Information (VGI), which is a direct geographic contribution by volunteers or affected residents, has the potential to provide the complementary information to the authoritative information. In this research, the author focused on text-based VGI that contains textual and spatial contents. Due to the potential for a large number of contributors, text-based VGI can be updated more quickly than authoritative sources and then provide valuable information for decision making. However, during a disaster, particularly an extreme event, the use of text-based VGI leads to both benefits and challenges. The volume of a text-based VGI collection is often huge. The stakeholders often lack scalability to identify high-quality content such as credible and informative information pieces. Text-based VGI is still underutilized in disaster response. Most of the existing efforts lack efficient methods for text-based VGI credibility and text content quality assessment. Specifically, the use of geographic characteristics of VGI in the process of quality assessment is rarely considered. To provide credible and informative content for disaster response efficiently, this thesis investigated a modelling approach for VGI quality assessment in a case study. The quality problem was treated as a classification problem. The VGI instances generated during two extreme flooding events in Brisbane were collected. Innovative data filtering processes and quality annotation processes were developed. Particularly, the correlation between quality and geographic characteristics of VGI instances was analysed and validated. Based on the annotated data, Supervised learning techniques were further employed for the development and evaluation of the quality assessment methods; the geographic method used the correlated geographic characteristics as the predictors, and the integrated method tested a combination of the geographic predictors and text-related predictors. The established approach that considered text contents only was used as a baseline method for the comparison. The developed experiments showed that the usage of geographic predictors can support the classification of high-quality VGI content more efficiently. The geographic method had an excellent performance in credibility assessment but was limited in text content quality assessment. On the other hand, the integrated method can be used in both credibility and text content quality assessment; models based on the integrated method can have better performance in comparison with the baseline method. The knowledge gained suggests great potential for using the developed methods to harvest VGI for the information needs of disaster response.

Building Information Modelling (BIM) plays an important role in the digital transformation of the construction sector and built environments. BIM promises to achieve better quality infrastructures and to shorten the duration of construction projects, and also has additional values in the global infrastructure market, as it potentially provides more efficiency in collaboration, transparency and information management, and greater intelligence in the decision-making process during the whole lifetime of buildings. In addition, up-to-date 3D building models serve as a versatile data source for various applications such as energy simulation, navigation, location-based services, and emergency response. Today, 3D building models are available only for newly designed or recently constructed buildings. A large proportion of existing buildings have been in existence for many decades. Meanwhile, the 3D models are not often updated to reflect changes in an existing building during the different stages of its lifecycle. Automated methods for efficient and reliable generation of 3D building models have the potential to expand the application domains to existing buildings. Although recent lidar scanning and photogrammetry techniques allow efficient capturing of the as-is condition of the built environment, the development of automated processes for the production of accurate, correct, and complete 3D models from the data remains a challenge. In addition, quantitative measurement of the quality of the 3D reconstructed models is essential, as it enables the measurement of the faithfulness of the models in representing the physical built environment. This thesis aims to develop a novel approach to automated reconstruction of indoor models and to provide a comprehensive method for quantitative evaluation of the quality and change detection of indoor models. The thesis contains three main contributions. First, a shape grammar approach for procedural modelling of indoor environment containing Manhattan world designs from lidar data is proposed. The hypothesis of this research is that understanding and translating the principles of indoor architectural design into a modelling algorithm will provide the capability to overcome the challenges and assist the reconstruction of a 3D semantic-rich model. Second, a procedural method for automated reconstruction of generic indoor models (i.e., Manhattan and non-Manhattan world buildings) using a stochastic approach is developed. The approach is based on a combination of a shape grammar and a data-driven approach, which facilitates the automated application of grammar rules in the production process and enhances its robustness to incomplete and inaccurate input. Third, a comprehensive method for quality evaluation, comparison, and change detection of 3D indoor models is proposed. The evaluation method facilitates a quantitative assessment of geometric quality of indoor models in terms of three quality aspects: completeness, correctness, and accuracy. The change detection method enables identification of redundant elements in existing 3D models and the missing elements in indoor environments. A series of experiments was carried out to evaluate the performance of the proposed methods on synthetic and real datasets, and the results show the capability of the methods for the reconstruction of complex indoor environments with high accuracy, completeness, and correctness.

Seismic hazard analysis and management for low-to-moderate seismicity regions is equally important as that for tectonic active regions of high seismicity. However, ground motion modelling for low-to-moderate seismicity regions can be challenging because the recordings of strong ground motions with the magnitude-distance ranges of engineering interests are at a paucity. This study mainly aims to develop a generic Ground Motion Prediction Equation (GMPE) that can be regionally adjustable for various low-to-moderate seismicity regions based on a synthetic ground motion dataset obtained from a number of stochastic simulations of updated seismological models. The stochastic simulation method is selected because of its simplicity and viability for low-to-moderate seismicity regions where abundant information of strong ground motions and geological settings is not available. A program (named Ground Motion Simulation System: GMSS) based on MATLAB-GUI is composed to make the process of stochastic simulation more transparent and user-friendly. The stochastic simulations of seismological models with various source parameters (stress drop and moment magnitude), path functions (geometric spreading and anelastic attenuation), and upper-crustal models (amplification and attenuation) are performed to construct a dataset that can be used for developing GMPE via regression techniques. A geology-based shear-wave velocity (VS) profiling model is proposed to construct the VS profile in a more comprehensive way. Six case studies are performed to validate that the profiling model is applicable in various crustal conditions. The VS profiles obtained from this model, combining with density profiles, can be used to model the frequency-dependent amplification factor that can be used in stochastic simulations. A generic GMPE, which is termed as Component Attenuation Model (CAM), is developed for use in low-to-moderate seismicity regions using the synthetic dataset. CAM decouples the earthquake generation process into three components: source, path, and crust. Each component is modelled, and the period-dependent coefficients are provided for constructing response spectra. CAM has been proved to be able to predict the field recorded ground motions collected from Switzerland with a reasonable level of accuracy. CAM is used to predict Peak Ground Velocity (PGV) for intraplate regions. Parameters of ground motion attenuation and local VS profiles are modelled for South-eastern Australia (SEA) and South-eastern China (SEC). Historical macro-seismic intensity (MMI) data is collected from the two intraplate regions to validate CAM as a generic regionally adjustable GMPE. CAM can be used as a solid tool for transforming seismological models into typical GMPEs, and as an independent regional/ local GMPE. The guidance of the engineering application of CAM is provided in Probabilistic Seismic Hazard Analysis (PSHA) and ground motion selection and scaling. A simplified PSHA approach based on the uniform seismicity assumption is adopted for South-eastern Australia condition in this study. Multiple GMPEs have been incorporated into PSHA to examine their performance when they are applied for SEA condition. The detailed procedures of ground motion selection and scaling (using Condition Spectrum (CS) as the target spectrum) are provided based on a combined GMPE and the PSHA deaggregation information. The selected ground motions from the NGA-West2 database on rock site can be used for the dynamic structural analysis and related further studies.

Groundwater is the world’s largest freshwater resource, constituting 96 % of available freshwater. However, overexploitation due to poor or absent management in many regions of the globe has resulted in adverse environmental and socio-economic impacts. Groundwater management seeks to balance and mitigate the detrimental impacts of development, and management plans are commonly used to outline strategies to share and distribute water. But, plans are seldom systematically and quantitatively assessed for effectiveness and many plans are not conducive to a quantitative evaluation. A comprehensive framework for evaluating plan effectiveness is lacking in hydrogeology and currently, it is unknow how effective many plans are at achieving their stated objectives. Because plans are the primary means of managing groundwater, it is crucial they are efficient and effective. The objective of this thesis was to develop a methodology to quantitatively evaluate the effectiveness of groundwater management plans and was conducted in three parts that each addressed one of the following research questions: 1. What components do plans require to be quantitatively assessed for effectiveness? 2. How can the effectiveness of groundwater management plans towards achieving objectives be evaluated? 3. How much calibration data is required to constrain model predictions so they are useful and informative? In chapter 3, groundwater management was structured as a system control problem to capture the feedback between an aquifer system and management action that occurs in reality, where management action is dictated by aquifer state. Within the control framework, a novel testability assessment rubric that determined if plans met the requirements of a control loop, and subsequently, whether they could be quantitatively tested, was developed. Seven components of a management plan equivalent to basic components of a control loop were determined, and the requirements necessary to enable testability were defined. Each component was weighted based upon proposed relative importance, then segmented into rated categories depending on how well the requirements were met. Component importance varied but, a defined objective or acceptable impact was necessary for plans to be testable. Plans lacking an objective or acceptable level of developmental impact could not be tested for effectiveness. The rubric was developed within the context of the Australian groundwater management industry, and while use of the rubric is not limited to Australia, it was applied to 15 diverse Australian groundwater management plans and approximately 47% were found to be testable. These results are significant because testability is an important, but often overlooked, prerequisite of the evaluation process and only by quantitatively assessing the effectiveness of groundwater management plans, can we systematically learn how to develop better management plans. Once it’s been established that a plan can be tested, the challenge of how to test it remains. This is the focus of chapter 4, where a plan testing methodology is developed using a numerical groundwater model. Historically, management modelling has focused on optimisation studies which quantify decision variables in order to find the “best” management strategies to create plans. In contrast, this study does not search for optimal strategies but instead, aims to simulate the sequential decision-making process implicit in environmental management, so that the effectiveness of management scenarios, when implemented as intended, can be evaluated. The purpose of this section was to develop and demonstrate a methodology to quantitatively evaluate the effectiveness of groundwater management plans by simulating sequential management decisions that evolve based on aquifer/management feedback. Groundwater management was structured as a system control loop to capture the aquifer/management feedback and management decisions were based on realistically sparse observation times and locations. The method provides an indication of how a plan may proceed in reality under alternate timings and frequencies of management decisions and in systems with differing response times. A synthetic example quantified the impact of a generic plan, specifying environmental objectives, extraction restrictions and entitlement limits, relative to no-management by combining a numerical model of reality with management rules under a stochastic climate. A simple synthetic model was used to demonstrate the methodology to test the effectiveness of sequential decision making in groundwater management. This allowed the effectiveness of a management plan to be evaluated within a system control framework. Model simplicity was chosen over site specific complexity to keep the results generalisable and avoid concentrating on case-specific idiosyncrasies. However, the method is easily extended to complex groundwater systems and management actions, provided they can be modelled adequately. The management decision-making frequency was varied from daily to decadal. Generally, effectiveness decreased as the interval between management interventions increased and intervals greater than annual showed minimal improvement compared to entitlement only. The timing of management decisions relative to the irrigation season also impacted plan effectiveness, and when decisions were made prior to the irrigation season, quarterly management was less effective than annual and biannual management. It was determined that the prediction of effectiveness was sensitive to model parameters (hydraulic conductivity). Considering that aquifers are vastly complex, heterogeneous, anisotropic systems this sensitivity to parameterisation cast doubt upon the utility of the methodology when applied to complex realistic scenarios. To investigate the feasibility of using this method considering the high degree of uncertainty in groundwater systems, chapter 5 comprised of a calibration constrained, predictive uncertainty analysis. Given the high degree of parameter uncertainty in groundwater models, section 3 (chapter 5) aimed to determine how much calibration data was necessary to quantitatively evaluate management plan effectiveness. A synthetic study was used to evaluate the uncertainty around predictions generated from four different groups of model realisations that were created based on increasing amounts of observation data, i.e. one prior model and three different posterior models. A numerical model of a synthetic, unconfined aquifer system ( reality) with domestic, monitoring and extractions wells was used to generate three calibration datasets (groundwater levels and extraction rates), that varied in length of time and monitoring network extents. The aquifer was managed by a management plan with the objective of preventing dewatering of a domestic well by implementing extraction restrictions in pumping wells when threshold groundwater level triggers were reached. The plan was considered to have failed if the well became dry. Management was simulated in the reality system for fifty years and a “true” plan effectiveness (number of failures) was produced and used as a baseline to compare prior and posterior models. Four simple models of the reality system were built based on alternatively, prior knowledge, and a calibrated solution to each of the three different observation datasets. Each model was used to predict the effectiveness of management decision-making on a monthly basis and if the aquifer was managed under a maximum entitlement volume, and finally, unmanaged. The model predictive uncertainty for the four simplified models of the synthetic reality system was quantified, through a calibration-constrained uncertainty analysis using Null-Space Monte Carlo methods. The objective was to evaluate if more extensive observation datasets can increase system understanding through calibration to such as degree that the plan effectiveness predictions approach the true reality effectiveness. Because models cannot simulate the true complexity of natural systems, simplifications are required. In this study, time-varying recharge that occurred in reality was simplified in the prior and posterior models as time-invariant, in line with standard industry practices. Due to the simplification of recharge, the hydraulic conductivity parameter assumed inappropriately high values during the calibration to compensate. This resulted in calibration-induced bias and caused the model to make erroneous predictions. Calibration-induced bias is difficult to identify because often an acceptable fit to data is achieved and does not indicate a problem. However, the calibrated model predicted that the plan would not fail, when in fact, the plan did fail, which has important repercussions for environmental management. Even with use of rigorous uncertainty analysis methods, the effectiveness of management could not be determined due to the limitations of numerical models which raised serious question over our ability to model management.

A number of seasonal solar thermal energy storage (SSTES) systems have been investigated for heating in cold climate locations due to the utilisation of solar energy. The system overcomes the drawback on the intermittency of solar energy and contributes to storing heat from summer to be used in winter. Heat pump and solar collectors with lower temperature thermal storage are the influencing factors to improve the system performance. A double U-tube borehole thermal energy storage (BTES) system integrated with ground coupled heat pump (GCHP) and evacuated tube solar collectors (ETSCs) is proposed for residential space heating in selected cold climate locations. Experimental data were collected from a double U-tube borehole heat exchanger (BHE) test rig; the data were used to validate the TRNSYS Type 257, which models double U-tube BHE. The performance of the proposed double U-tube BTES-GCHP-ETSC system was evaluated by computer simulations. A cluster of 30 residential houses in six selected cold climate locations: Lukla (Nepal), Dras (India), Sivas (Turkey), Harbin (China), Ulaanbaatar (Mongolia) and Verkhoyansk (Russia) were investigated. The design variables of the proposed system were optimised to minimise total life cycle cost (TLCC) and total life cycle greenhouse gas emissions (TLCG). The initial investigation was to provide a detailed review of various parameters (options) of SSTES systems. The BTES system has better energy performance with relatively low cost compare with other thermal storage systems. The lower temperature SSTES system may be more suitable for the cold climate conditions. However, the lower temperature stored heat cannot be directly used for space heating, and a heat pump needs to be coupled to upgrade the temperature of the delivered heat. The SSTES system is a promising technique for cold climate locations with adequate solar radiations. It was found that the annual average heating coefficient of performance (COP) of the heat pump, COP of the system, and the ground temperature are increased by adding solar collectors to a conventional heat pump (HP) system. In contrast, the required borehole depth, heat pump energy consumption and extracted energy from the ground are decreased due to the inclusion of solar collectors in the system. The highest COP of a heat pump is found at a system with ETSC compared to other solar collectors. Furthermore, double U-tube BHE has lower LCC and higher heat transfer rate than single U-tube BHE configuration. An experimental study was conducted to validate the TRNSYS Type 257. All system components, pipe network, data acquisition systems, operation procedures and schedules, weather station and measuring instrument were described. The experiments were conducted for heat charging and space heating operations. The measured undisturbed ground temperature (UGT) at the experiment site was presented. The UGT were found to be 17.64 degree celsius and 17.68 degree celsius at 21 m and 40 m depth respectively. The validation of the double U-tube BHE model was presented. The simulated and measured temperatures were compared. Statistical parameters: mean bias error (MBE), root mean square error (RMSE) and correlation coefficient (CC) were used to quantify the agreements between the simulated and measured data. Both heat charging mode and space heating mode models were validated. The duration for the comparison was one-week for both operation modes. The CC of double U-tube BHE model was found to be 0.99 and 0.91 for heat charging mode and space heating mode respectively. The MBE were found to be 0.15 and -0.07 for heat charging mode and space heating mode respectively. The RMSE were 0.37 and 0.51 for heat charging mode and space heating mode respectively. A TRNSYS model was developed to simulate the proposed BTES-GCHP-ETSC system for a cluster of residential houses in selected six cold climate locations. The residential house model for each location was developed based on the typical local dwelling. It was found that the annual heating loads per unit floor area (in GJ m-2) are: 1.71, 1.79, 0.71, 1.19, 1.45 and 2.59 for, Lukla, Sivas, Dras, Harbin, Ulaanbaatar and Verkhoyansk respectively. The system was investigated for heat charging and space heating (heat discharging) modes where the ground temperature and heat losses were analysed. The results of the simulation over 20 years period showed that the average ground temperatures were stable in each location with solar charging option. The energy balance of the system at the 20th year was analysed. The highest seasonal compressor heating coefficient of performance (SHCOP) was found to be 6.65 at Lukla and lowest was 6.03 at Sivas. On the other hand, the highest COPsys (4.39) was found at Verkhoyansk and lowest (2.68) at the Sivas. It was found that the proposed system fulfils the 95%, 92%, 93%, 93%, 96% and 100% of space heating demand for Lukla, Sivas, Dras, Harbin, Ulaanbaatar and Verkhoyansk respectively. The TRNSYS simulation model coupled with multi-objective building optimisation (MOBO) software was used to optimise system variables. There are three separate optimisation investigations: two single objective and one multi objectives for the system. The first investigation is to minimise total life cycle greenhouse gas emissions (TLCG, t), and the second investigation is to minimise total life cycle cost (TLCC, $) included cost of GHGE. The third investigation is to minimise both life cycle cost (LCCRsysR) of system and cost of greenhouse gas emissions (Cghge) (multi objectives). The optimum proposed system configuration (total solar collector area, number of boreholes and total borehole length were determined. The annual life cycle cost (ALCC), the unit heating cost (UHC), net energy ratio (NER), simple payback time (SPBT), carbon payback time (CPBT), and energy payback time (EPBT) were determined to analyse the proposed SSTES system. The proposed SSTES system was optimised for minimising TLCG, where total amount of embodied and operational GHGE were considered for 20 years project life. The maximum GHGE was found at Dras and the minimum at Lukla. The maximum ALCC was found at Verkhoyansk and the minimum at Sivas. The maximum UHC was found at Sivas and the minimum at Verkhoyansk because the size of the heating system is larger at Verkhoyansk than other location. The maximum CPBT and SPBT were found at Sivas and the minimum at Lukla. The EPBT was found highest at Sivas where NER was found lowest. On the other hand, the EPBT was found lowest at Ulaanbaatar where NER was found highest. The maximum SHCOP and COPsys were found at Lukla and Dras respectively. In addition, the proposed BTES-GCHP-ETSC system was optimised for minimising TLCC for 20 years project life, where the system cost and cost of GHGE were considered. The maximum total life cycle cost (TLCC) (cost of system and GHGE) was found at Verkhoyansk and the minimum at Sivas. The operational cost was found highest at Verkhoyansk than other locations because the pumps operate longer to meet the heating demand. The cost of GHGE was the height at Dras and the lowest at Lukla. The ALCC was maximum at Verkhoyansk and minimum at Sivas. The maximum UHC was found at Sivas and the minimum at Verkhoyansk. The NER was found to be the height at Verkhoyansk and the lowest at Sivas. The maximum SPBT was found at Sivas and the minimum at Lukla. The minimum EPBT was found at Verkhoyansk and maximum at Sivas. The SHCOP were found to be 7.00, 6.03, 6.72, 6.22, 6.12 and 6.45 for Lukla, Sivas, Dras, Harbin, Ulaanbaatar and Verkhoyansk respectively. The COPsys were found to be 3.23 (Lukla), 3.57 (Dras), 2.68 (Sivas), 3.53 (Harbin), 3.52 (Ulaanbaatar) and 4.39 (Verkhoyansk). Further, multi-objectives optimisation of SSTES system for space heating in cold climate locations was investigated. Multi-objective functions were applied to determine the Pareto front of variables. The LCCsys and the Cghge were the two objective functions. The minimum LCCsys and the minimum Cghge points as the Pareto fronts were determined. However, minimum TLCC points have 53% (Lukla), 37% (Dras) and 42% (Ulaanbaatar) shorter borehole length than minimum TLCG points.

Fragranced consumer products—such as cleaning supplies, air fresheners, and personal care products— emit numerous volatile organic compounds (VOCs), some classified as potentially hazardous. In addition, emissions from fragranced products can be a primary contributor to indoor and outdoor air pollutants, and human exposure risks. Further, exposure to volatile emissions from fragranced products has been associated with adverse human health effects in approximately one-third of Australians. However, fragranced products are exempt from full ingredient disclosure, thus limiting information and awareness about emissions. Moreover, relatively little prior research has analysed emissions from these products. The overall aim of this thesis research is to investigate volatile emissions from a wide range of fragranced consumer products. As a three-part research study, it investigates VOCs emitted from 200 products in three groups: 42 baby products, 24 essential oils, and 134 consumer products. Products include both regular versions and those with claims of being green or related terms such as organic or natural. Volatile emissions from each individual product were analysed using headspace gas chromatography/mass spectrometry. Overall, the study found 2,817 VOCs, including 848 potentially hazardous VOCs, emitted from the 200 products. Specifically, for each group of products, the study found (1) 684 VOCs including 207 potentially hazardous VOCs in baby products; (2) 589 VOCs including 124 potentially hazardous VOCs in essential oils; and (3) 1,538 VOCs including 517 potentially hazardous VOCs in consumer products. Across the 200 products, fewer than 4% of VOCs and 9% of potentially hazardous VOCs were disclosed by being listed on product labels. For each of the three groups of products, emissions of potentially hazardous VOCs were not significantly different between regular and green fragranced products. This dissertation research provides contributions to knowledge through the analysis and comparison of relatively large number and diversity of products, a broad suite of VOCs, compounds classified as potentially hazardous, and both regular and green products. Results from this research provide new knowledge on volatile emissions from consumer products, which can improve awareness of potential exposures and effects on air quality, health, and societal well-being.

The global food requirement has increased by 70% over the last century and the challenge of feeding an additional 2 billion people by 2030 is further intensifying the pressure on food production and irrigated agriculture. Consequently, stress on water resources is increasing, particularly on groundwater, which caters for about half of the global irrigation. Despite irrigated agriculture being the largest consumer of groundwater and a clear cause of groundwater depletion, quantitative knowledge about the link between these two is limited. In order to address this gap, this research investigates the relationship between groundwater depletion and groundwater dependent agriculture, particularly food production, at the global scale. After an introduction and detailed literature review, this research is presented in three parts: 1) developing a groundwater recharge model to estimate the global groundwater potential, 2) evaluating the current groundwater stress due to food production and 3) exploring future groundwater stress under different climate change scenarios. Part 1 (Chapter 3) identified the most influential factors affecting diffuse groundwater recharge and developed an empirical model to estimate recharge at the global-scale. Recharge estimates reported in the literature from various parts of the world (715 sites) were compiled and used in model development and testing. Unlike conventional recharge estimates from water balance, a multi-model inference approach and information theory were used to select predictors and determine an empirical relationship between groundwater recharge and the most important predictors. Meteorological factors (precipitation and potential evapotranspiration) and vegetation factors (land use and land cover) were found to have the most predictive power for recharge estimation. The recharge model developed using the most influential factors was tested at different spatial scales and was applied globally at 0.5 deg resolution and annual timestep. The model showed acceptable performance in predicting long term groundwater recharge. At 97% of the testing sites the error in prediction ranged from -8 mm/y to 10 mm/y. Having developed a model to estimate the global groundwater recharge, the current and future stress on the groundwater resources due to irrigated food production was investigated in Part 2 (Chapter 4) and Part 3 (Chapter 5). In Part 2, the stress on groundwater systems was analysed by calculating the ratio between groundwater use and availability, allowing for environmental baseflow requirements. The groundwater extraction potential or groundwater availability was determined using the recharge model developed in Part 1 and the irrigation water demand from a global soil water balance model, GlobWAT. Additionally, various pathways for stress reduction via improved irrigation efficiency and increased crop productivity were explored in this part. From this study, it was found that of 63 countries utilizing groundwater for irrigation, one third of them are overexploiting groundwater resources, while the groundwater in one-fifth of them is moderately to heavily stressed. Moreover, the groundwater stress is mostly focused on a few of the heavily populated areas including the North China Plain, North-west India and Central USA. About 450 million tonnes of global annual food production is produced from non-renewable groundwater exploitation. Increases in irrigation efficiency and irrigation productivity were found to be effective in reducing but not eliminating groundwater stress without compromising food security under current population. By increasing the global irrigation efficiency to 90%, groundwater stress in the most severely affected areas could be reduced by 40%. The improved efficiency would also mean that additional food could be produced from the part of groundwater sustainably extracted. Additionally, improved irrigation productivity (increasing the food produced per unit of water extracted) in conjunction with increased irrigation efficiency could reduce the current level of unsustainable food production by three quarters. Part 3 (Chapter 5) investigates the future status of groundwater resources and associated unsustainable food production under climate change. The climate change impact on groundwater resources was investigated by forcing the groundwater recharge model developed in Part 1 and the GlobWAT irrigation demand model with HadGEM2-ES General Circulation Model (GCM) outputs from phase 5 of the Coupled Model Intercomparison Project (CMIP5). The analysis was done from 2006 to 2100 for Representative Concentration Pathways (RCP) 4.5 and 8.5. This chapter followed the same methods used in Chapter 4 with the future climate data. It was found that both irrigation water requirement met from groundwater (+7%) and the groundwater available for extraction (+3%) would increase in the future under these scenarios. The gap between the water demand and water availability increases, leading to greater stress on groundwater resources globally. Under future food demand, by 2080, 25% (RCP 4.5) and 29% (RCP 8.5) of the total food produced from groundwater would have to be met by overusing the groundwater resources. Regional variability in these global trends was also explored. The results from this thesis give key insights into the dynamics of irrigation stress on groundwater systems and identify hotspots of groundwater stress across the globe. This information is crucial to evidence-based management of groundwater and also to meeting the needs of current and future populations.