Infrastructure Engineering - Research Publications
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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.
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ItemEvolution of the human-water relationships in the Heihe River basin in the past 2000 years(COPERNICUS GESELLSCHAFT MBH, 2015)Abstract. This paper quantitatively analyzed the evolution of human–water relationships in the Heihe River basin of northern China over the past 2000 years by reconstructing the catchment water balance by partitioning precipitation into evapotranspiration and runoff. The results provided the basis for investigating the impacts of societies on hydrological systems. Based on transition theory and the rates of changes of the population, human water consumption and the area of natural oases, the evolution of human–water relationships can be divided into four stages: predevelopment (206 BC–AD 1368), take-off (AD 1368–1949), acceleration (AD 1949–2000), and the start of a rebalancing between human and ecological needs (post AD 2000). Our analysis of the evolutionary process revealed that there were large differences in the rate and scale of changes and the period over which they occurred. The transition of the human–water relationship had no fixed pattern. This understanding of the dynamics of the human–water relationship will assist policy makers in identifying management practices that require improvement by understanding how today's problems were created in the past, which may lead to more sustainable catchment management in the future.
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ItemAssimilation of stream discharge for flood forecasting: Updating a semidistributed model with an integrated data assimilation scheme(AMER GEOPHYSICAL UNION, 2015-05)Abstract Real‐time discharge observations can be assimilated into flood models to improve forecast accuracy; however, the presence of time lags in the routing process and a lack of methods to quantitatively represent different sources of uncertainties challenge the implementation of data assimilation techniques for operational flood forecasting. To address these issues, an integrated error parameter estimation and lag‐aware data assimilation (IEELA) scheme was recently developed for a lumped model. The scheme combines an ensemble‐based maximum a posteriori (MAP) error estimation approach with a lag‐aware ensemble Kalman smoother (EnKS). In this study, the IEELA scheme is extended to a semidistributed model to provide for more general application in flood forecasting by including spatial and temporal correlations in model uncertainties between subcatchments. The result reveals that using a semidistributed model leads to more accurate forecasts than a lumped model in an open‐loop scenario. The IEELA scheme improves the forecast accuracy significantly in both lumped and semidistributed models, and the superiority of the semidistributed model remains in the data assimilation scenario. However, the improvements resulting from IEELA are confined to the outlet of the catchment where the discharge observations are assimilated. Forecasts at “ungauged” internal locations are not improved, and in some instances, even become less accurate.
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ItemBalancing Rural Household Livelihood and Regional Ecological Footprint in Water Source Areas of the South-to-North Water Diversion Project(MDPI AG, 2017-08)There is a knowledge gap and practical demand to understand the co-evolutionary relationship between rural household livelihood and regional ecological footprints for developing sustainable livelihoods in ecological conservation regions. This paper tracks the change trajectories of rural household livelihoods and regional ecological footprints in four water source areas of the South-to-North Water Diversion Project where various ecological and environmental protection projects and measures are being proposed to protect water quality. As a result, some concerns regarding rural livelihood have arisen. The sustainable livelihood approach developed by DFID (Department for International Development in UK) was used to measure the natural, physical, financial, human, and social capitals of rural livelihoods, while the ecological footprint accounting approach was used to calculate the amount of bio-productive spaces that produce the yearly resource flows for human consumption. The study period is 2000–2014 and data was obtained from the Statistical Yearbooks. The results show that the change trend of natural capitals of rural households, which have increased by 72.5% (SY), 98.8% (NY), 69.3% (TA), and 120.3% (JN) within 15 years, determine the overall change track of rural livelihoods and that rural household livelihood grows with the expansion of regional ecological footprints. Sensitivity of regional eco-footprints to rural livelihood varies from 5.8 to 0.5 in case areas. It is recommended that in the “post South-to-North Water Diversion era”, four policy instruments—population transfer and relocation, industrial restructuring and updating, rural infrastructure and community reconstruction, and cross-ecological compensation—should be adopted to improve sustainable livelihoods in these four water source areas.
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ItemKey factors influencing differences in stream water quality across space(WILEY, 2018-01-01)Globally, many rivers are experiencing declining water quality, for example, with altered levels of sediments, salts, and nutrients. Effective water quality management requires a sound understanding of how and why water quality differs across space, both within and between river catchments. Land cover, land use, land management, atmospheric deposition, geology and soil type, climate, topography, and catchment hydrology are the key features of a catchment that affect: (1) the amount of suspended sediment, nutrient, and salt concentrations in catchments (i.e., the source), (2) the mobilization ,and (3) the delivery of these constituents to receiving waters. There are, however, complexities in the relationship between landscape characteristics and stream water quality. The strength of this relationship can be influenced by the distance and spatial arrangement of constituent sources within the catchment, cross correlations between landscape characteristics, and seasonality. A knowledge gap that should be addressed in future studies is that of interactions and cross correlations between landscape characteristics. There is currently limited understanding of how the relationships between landscape characteristics and water quality responses can shift based on the other characteristics of the catchment. Understanding the many forces driving stream water quality and the complexities and interactions in these forces is necessary for the development of successful water quality management strategies. This knowledge could be used to develop predictive models, which would aid in forecasting of riverine water quality. WIREs Water 2018, 5:e1260. doi: 10.1002/wat2.1260 This article is categorized under: Science of Water > Hydrological Processes Science of Water > Water Quality
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ItemThe value of water in storage: Implications for operational policies(Curran Associate Inc., 2018-01-01)With desalination plants becoming an increasingly common feature of water supply systems for major cities, the options for managing water security are now markedly different to past times when the short-term response to low water availability essentially revolved around reducing usage. The operation of desalination plants and other components of diversified water supply systems now enable operators to increase availability, essentially by producing water. The operation of such systems clearly impacts operational costs but, more subtly, also impacts future augmentation decisions. This can have major cost implications as there is a trade-off between the costs of operating a water supply system and the probability and timing of future augmentations that leads to important differences in the economics of reliably supplying water. This paper first summarises an economic analysis framework in which to explore the interaction of short (operational) and long (capital investment) term decisions towards maintaining water security. It then explores the implications of different operation approaches in Melbourne’s water supply system, assuming a planned augmentation pathway under conditions of low water availability. We assume augmentation decisions are prompted by critically low water availability events, rather than long-term reliability analysis. We show that the majority of the variation in cost of maintaining a reliable water supply is associated with impacts of operational rules on likely capital investment and that this results in a strong interaction between short and long-term decision making. The outcome of this work has implications for both operational decision making and augmentation planning for urban water supply systems. These implications are relevant to any water supply system where a climate independent water supply source, such as desalination, can be accessed.
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ItemAn evaluation of a methodology for seasonal soil water forecasting for Australian dry land cropping systems(ELSEVIER, 2018-05-01)Soil water is a critical resource in many rain-fed agricultural systems. Climate variability represents a significant risk in these systems, which has been addressed in the past through seasonal weather outlooks. This study undertakes a pilot assessment of the potential to extend seasonal weather outlooks to plant available soil water (PASW). We analyse 20 sites in the southeast Australian wheat belt using seasonal weather outlooks from the Predictive Ocean-Atmosphere Model for Australia (POAMA; (the operational seasonal model of the Australian Bureau of Meteorology), which were downscaled and used in conjunction with the Agricultural Production Simulator (APSIM). Hindcast rainfall, potential evapotranspiration (PET) and PASW outlooks were produced on a monthly basis for 33 years at a point scale. The outlooks were assessed using a range of ensemble verification tools. The results showed hit rates that outperformed climatology for rainfall and PET in the short-term (0–2 months), and for PASW with longer lead times (2–5 months). Continuous rank probability skill scores (CRPSS) were generally statistically worse than climatology for rainfall and PET and statistically better than climatology for PASW over 1–3 months. The influence of initial soil water is seasonally dependent, with longer dependence in low evapotranspiration periods. Improved weather model downscaling approaches would transition to climatology and could improve both weather and PASW outlooks. PASW outlooks were strongly reliant on initial conditions, indicating the importance of understanding current soil water status, which needs to be interpreted in a seasonal context as its influence varies over the year. Expanded operational soil water monitoring would be important if PASW outlooks are to become routine.
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ItemPredicting groundwater recharge for varying land cover and climate conditions - a global meta-study(COPERNICUS GESELLSCHAFT MBH, 2018-05-07)Abstract. Groundwater recharge is one of the important factors determining the groundwater development potential of an area. Even though recharge plays a key role in controlling groundwater system dynamics, much uncertainty remains regarding the relationships between groundwater recharge and its governing factors at a large scale. Therefore, this study aims to identify the most influential factors of groundwater recharge, and to develop an empirical model to estimate diffuse rainfall recharge at a global scale. Recharge estimates reported in the literature from various parts of the world (715 sites) were compiled and used in model building and testing exercises. Unlike conventional recharge estimates from water balance, this study used a multimodel inference approach and information theory to explain the relationship between groundwater recharge and influential factors, and to predict groundwater recharge at 0.5∘ resolution. The results show that meteorological factors (precipitation and potential evapotranspiration) and vegetation factors (land use and land cover) had the most predictive power for recharge. According to the model, long-term global average annual recharge (1981–2014) was 134 mm yr−1 with a prediction error ranging from −8 to 10 mm yr−1 for 97.2 % of cases. The recharge estimates presented in this study are unique and more reliable than the existing global groundwater recharge estimates because of the extensive validation carried out using both independent local estimates collated from the literature and national statistics from the Food and Agriculture Organization (FAO). In a water-scarce future driven by increased anthropogenic development, the results from this study will aid in making informed decisions about groundwater potential at a large scale.
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ItemJustin Costelloe: a champion of arid-zone water research(Springer Verlag, 2019-11-06)Justin Francis Costelloe (Fig. 1) was born in 1965. He grew up in the mining city of Bendigo (Victoria, Australia) before studying Earth Sciences at the University of Melbourne. He went on to work as an exploration geologist in the mining industry in the dryland regions of Australia and Chile. He developed a love of Australia’s desert landscapes and returned to undertake Masters and PhD studies on arid zone hydrology at the University of Melbourne, before continuing as a research fellow and senior research fellow leading arid zone research projects. Justin was a leader in research aimed at understanding surface water and groundwater in Australia’s arid zone and also made important interdisciplinary contributions linking the hydrology and ecology of the arid zone, with a focus on Australia’s iconic Channel Country and the Great Artesian Basin (GAB).
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ItemPredicting shifts in rainfall-runoff partitioning during multiyear drought: Roles of dry period and catchment characteristics(AMER GEOPHYSICAL UNION, 2016-12)Abstract While the majority of hydrological prediction methods assume that observed interannual variability explores the full range of catchment response dynamics, recent cases of prolonged climate drying suggest otherwise. During the ∼decade‐long Millennium drought in south‐eastern Australia significant shifts in hydrologic behavior were reported. Catchment rainfall‐runoff partitioning changed from what was previously encountered during shorter droughts, with significantly less runoff than expected occurring in many catchments. In this article, we investigate the variability in the magnitude of shift in rainfall‐runoff partitioning observed during the Millennium drought. We re‐evaluate a large range of factors suggested to be responsible for the additional runoff reductions. Our results suggest that the shifts were mostly influenced by catchment characteristics related to predrought climate (aridity index and rainfall seasonality) and soil and groundwater storage dynamics (predrought interannual variability of groundwater storage and mean solum thickness). The shifts were amplified by seasonal rainfall changes during the drought (spring rainfall deficits). We discuss the physical mechanisms that are likely to be associated with these factors. Our results confirm that shifts in the annual rainfall‐runoff relationship represent changes in internal catchment functioning, and emphasize the importance of cumulative multiyear changes in the catchment storage for runoff generation. Prolonged drying in some regions can be expected in the future, and our results provide an indication of which catchments characteristics are associated with catchments more susceptible to a shift in their runoff response behavior.