Infrastructure Engineering - Research Publications
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ItemManaging risks associated with environmental water delivery: a case study of the Goulburn River, Australia(ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD, 2024-01-01)
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ItemNo Preview AvailableBalancing observational data and experiential knowledge in environmental flows modeling(Elsevier BV, 2024-02-01)
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ItemNo Preview AvailableExploring the role and decision-making behavior of irrigation water supply authorities in Australia(ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD, 2023-03-04)
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ItemNo Preview AvailableBasin-scale riverine ecosystem services vary with network geometry(ELSEVIER, 2023-10)
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ItemNo Preview AvailableThe Music of Rivers: The Mathematics of Waves Reveals Global Structure and Drivers of Streamflow Regime(AMER GEOPHYSICAL UNION, 2023-07)Abstract River flows change on timescales ranging from minutes to millennia. These vibrations in flow are tuned by diverse factors globally, for example, by dams suppressing multi‐day variability or vegetation attenuating flood peaks in some ecosystems. The relative importance of the physical, biological, and human factors influencing flow is an active area of research, as is the related question of finding a common language for describing overall flow regime. Here, we addressed both topics using a daily river discharge data set for over 3,000 stations across the globe from 1988 to 2016. We first studied similarities between common flow regime quantification methods, including traditional flow metrics, wavelets, and Fourier analysis. Across all these methods, the flow data showed low‐dimensional structure (i.e., simple and consistent patterns), suggesting that fundamental mechanisms are constraining flow regime. One such pattern was that day‐to‐day variability was negatively correlated with year‐to‐year variability. Additionally, the low‐dimensional structure in river flow data correlated closely with only a small number of catchment characteristics, including catchment area, precipitation, and temperature—but notably not biome, dam surface area, or number of dams. We discuss these findings in a framework intended to be accessible to the many communities engaged in river research and management, while stressing the importance of letting structure in data guide both mechanistic inference and interdisciplinary discussion.
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ItemNo Preview AvailableThe time of emergence of climate-induced hydrologic change in Australian rivers(ELSEVIER, 2023-04)
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ItemNo Preview AvailableApplying and Assessing Participatory Approaches in an Environmental Flows Case Study(SPRINGER, 2023-10)Environmental flows (e-flows) management takes place within a complex social-ecological system, necessitating the involvement of diverse stakeholders and an appreciation of a range of perspectives and knowledge types. It is widely accepted that incorporating participatory methods into environmental flows decision-making will allow stakeholders to become meaningfully involved, improving potential solutions, and fostering social legitimacy. However, due to substantial structural barriers, implementing participatory approaches can be difficult for water managers. This paper assesses the effectiveness of an e-flows methodology that combines elements of structured decision-making and participatory modeling, whilst constrained by project resources. Three process-based objectives were identified by the group at the start of the process: improving transparency, knowledge exchange, and community ownership. We evaluated the success of the approach according to those objectives using semi-structured interviews and thematic analysis. In evaluating how well the participatory approach achieved the process objectives, we found that at least 80% of respondents expressed positive sentiment in every category (n = 15). We demonstrate that the values-based process objectives defined by the participant group are an effective tool for evaluating participatory success. This paper highlights that participatory approaches can be effective even in resource-constrained environments when the process is adapted to fit the decision-making context.
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ItemModelling Impacts of Environmental Water on Vegetation of a Semi-Arid Floodplain-Lakes System Using 30-Year Landsat Data(MDPI, 2022-02)River floodplains are among the most dynamic and diverse ecosystems on the planet. They are at risk of degradation due to river regulation and climate change. Environmental water has been delivered to floodplains to maintain environmental health by mimicking natural floods. It is important to understand the long-term effects of environmental water to floodplain vegetation to support its management. This study used Normalized Differences Vegetation index (NDVI) from the 30-year Landsat datasets of the Hattah Lakes floodplain in Australia to investigate the drivers of vegetation dynamics. We developed generalized additive mixed models (GAMM) to model responses of vegetation to environmental water, natural floods, precipitation, temperature, and distance to water across multiple spatial and temporal scales. We found the effect of environmental water on floodplain vegetation to be quite different from that of natural floods in both space and time. Vegetation in most areas of Hattah Lakes will respond to natural floods within one month of flooding, while positive responses to environmental water occur 1 to 3 months after inundation and are more restricted spatially. For environmental water planning, managers need to be aware of these differences. The implementation of new infrastructure to transport or retain environmental water on floodplains needs to be planned carefully, with continuous monitoring of rainfall and natural floods. Whilst environmental floods do not mimic the effect of natural floods, they do provide some positive benefits that can partially offset effects of reduced natural floods.
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ItemNot Just Another Assessment Method: Reimagining Environmental Flows Assessments in the Face of Uncertainty(FRONTIERS MEDIA SA, 2022-05-10)The numerous environmental flows assessment methods that exist typically assume a stationary climate. Adaptive management is commonly put forward as the preferred approach for managing uncertainty and change in environmental flows. However, we contend that a simple adaptive management loop falls short of meeting the challenges posed by climate change. Rather, a fundamental rethink is required to ensure both the structure of environmental flows assessments, along with each individual technical element, actively acknowledges the multiple dimensions of change, variability and complexity in socio-ecological systems. This paper outlines how environmental flow assessments can explicitly address the uncertainty and change inherent in adaptively managing multiple values for management of environmental flows. While non-stationarity and uncertainty are well recognised in the climate literature, these have not been addressed within the structure of environmental flows methodologies. Here, we present an environmental flow assessment that is structured to explicitly consider future change and uncertainty in climate and socio-ecological values, by examining scenarios using ecological models. The environmental flow assessment methodology further supports adaptive management through the intentional integration of participatory approaches and the inclusion of diverse stakeholders. We present a case study to demonstrate the feasibility of this approach, highlighting how this methodology facilitates adaptive management. Rethinking our approach to environmental flows assessments is an important step in ensuring that environmental flows continue to work effectively as a management tool under climate change.
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ItemNo Preview AvailableA predictive model for spatio-temporal variability in stream water quality( 2019-07-23)Abstract. Degraded water quality in rivers and streams can have large economic, societal and ecological impacts. Stream water quality can be highly variable both over space and time. To develop effective management strategies for riverine water quality, it is critical to be able to predict these spatio-temporal variabilities. However, our current capacity to model stream water quality is limited, particularly at large spatial scales across multiple catchments. This is due to a lack of understanding of the key controls that drive spatio-temporal variabilities of stream water quality. To address this, we developed a Bayesian hierarchical statistical model to analyse the spatio-temporal variability in stream water quality across the state of Victoria, Australia. The model was developed based on monthly water quality monitoring data collected at 102 sites over 21 years. The modelling focused on six key water quality constituents: total suspended solids (TSS), total phosphorus (TP), filterable reactive phosphorus (FRP), total Kjeldahl nitrogen (TKN), nitrate-nitrite (NOx), and electrical conductivity (EC). Among the six constituents, the models explained varying proportions of variation in water quality. EC was the most predictable constituent (88.6 % variability explained) and FRP had the lowest predictive performance (19.9 % variability explained). The models were validated for multiple sets of calibration/validation sites and showed robust performance. Temporal validation revealed a systematic change in the TSS model performance across most catchments since an extended drought period in the study region, highlighting potential shifts in TSS dynamics over the drought. Further improvements in model performance need to focus on: (1) alternative statistical model structures to improve fitting for the low concentration data, especially records below the detection limit; and (2) better representation of non-conservative constituents by accounting for important biogeochemical processes. We also recommend future improvements in water quality monitoring programs which can potentially enhance the model capacity, via: (1) improving the monitoring and assimilation of high-frequency water quality data; and (2) improving the availability of data to capture land use and management changes over time.