Infrastructure Engineering - Research Publications
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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, 2016-12-01)
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ItemEquifinality and Flux Mapping: A New Approach to Model Evaluation and Process Representation Under Uncertainty(AMER GEOPHYSICAL UNION, 2019-11-12)
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ItemNo Preview AvailableEquifinality and process-based modelling(American Geophysical Union, 2018-11-26)Equifinality is understood as one of the fundamental difficulties in the study of open complex systems, including catchment hydrology. A review of the hydrologic literature reveals that the term equifinality has been widely used, but in many cases inconsistently and without coherent recognition of the various facets of equifinality, which can lead to ambiguity but also methodological fallacies. Therefore, in this study we first characterise the term equifinality within the context of hydrological modelling by reviewing the genesis of the concept of equifinality and then presenting a theoretical framework. During past decades, equifinality has mainly been studied as a subset of aleatory (arising due to randomness) uncertainty and for the assessment of model parameter uncertainty. Although the connection between parameter uncertainty and equifinality is undeniable, we argue there is more to equifinality than just aleatory parameter uncertainty. That is, the importance of equifinality and epistemic uncertainty (arising due to lack of knowledge) and their implications is overlooked in our current practice of model evaluation. Equifinality and epistemic uncertainty in studying, modelling, and evaluating hydrologic processes are treated as if they can be simply discussed in (or often reduced to) probabilistic terms (as for aleatory uncertainty). The deficiencies of this approach to conceptual rainfall-runoff modelling are demonstrated for selected Australian catchments by examination of parameter and internal flux distributions and interactions within SIMHYD. On this basis, we present a new approach that expands equifinality concept beyond model parameters to inform epistemic uncertainty. The new approach potentially facilitates the identification and development of more physically plausible models and model evaluation schemes particularly within the multiple working hypotheses framework, and is generalisable to other fields of environmental modelling as well.
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ItemCompounding Impacts of Human-Induced Water Stress and Climate Change on Water Availability(NATURE PUBLISHING GROUP, 2017-07-24)The terrestrial phase of the water cycle can be seriously impacted by water management and human water use behavior (e.g., reservoir operation, and irrigation withdrawals). Here we outline a method for assessing water availability in a changing climate, while explicitly considering anthropogenic water demand scenarios and water supply infrastructure designed to cope with climatic extremes. The framework brings a top-down and bottom-up approach to provide localized water assessment based on local water supply infrastructure and projected water demands. When our framework is applied to southeastern Australia we find that, for some combinations of climatic change and water demand, the region could experience water stress similar or worse than the epic Millennium Drought. We show considering only the influence of future climate on water supply, and neglecting future changes in water demand and water storage augmentation might lead to opposing perspectives on future water availability. While human water use can significantly exacerbate climate change impacts on water availability, if managed well, it allows societies to react and adapt to a changing climate. The methodology we present offers a unique avenue for linking climatic and hydrologic processes to water resource supply and demand management and other human interactions.
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ItemAssessing the degree of hydrologic stress due to climate change(Springer (part of Springer Nature), 2019-09-01)Hydrologists are commonly involved in impact, adaption and vulnerability assessments for climate change projections. This paper presents a framework for how such assessments can better differentiate between the impacts of climate change and those of natural variability, an important differentiation as it relates to the vulnerability to water availability under change. The key concept involved is to characterize “hydrologic stress” relative to the range of behaviour encountered under baseline conditions, where the degree to which climate change causes the behaviour of a system to shift outside this baseline range provides a non-dimensional measure of stress. The concept is applicable to any system that is subject to climate forcings, though the approach is applied here to a range of examples illustrative of many environmental and engineering applications. These include hydrologic systems that are dependent on the frequency of flows above or below selected thresholds, those that are dominated by storage and those which are sensitive to the sequencing of selected flow components. The analyses illustrate that systems designed or adapted to accommodate high variability are less stressed by a given magnitude of climate impacts than those operating under more uniform conditions. The metrics characterize hydrologic stress in a manner that can facilitate comparison across different regions, or across different assets within a region. Adoption of the approach requires reliance on the use of climate ensembles that represent aleatory uncertainty under both baseline and impacted conditions, and this has implications for how the outputs of climate models are provided and utilized.
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ItemModular Assessment of Rainfall-Runoff Models Toolbox (MARRMoT) v1.2: An open-source, extendable framework providing implementations of 46 conceptual hydrologic models as continuous state-space formulations(Copernicus Publications, 2019-06-25)This paper presents the Modular Assessment of Rainfall-Runoff Models Toolbox (MARRMoT): A modular open-source toolbox containing documentation and model code based on 46 existing conceptual hydrologic models. The toolbox is developed in MATLAB and works with Octave. MARRMoT models are based solely on traceable published material and model documentation, not on already-existing computer code. Models are implemented following several good practices of model development: The definition of model equations (the mathematical model) is kept separate from the numerical methods used to solve these equations (the numerical model) to generate clean code that is easy to adjust and debug; the implicit Euler time-stepping scheme is provided as the default option to numerically approximate each model's ordinary differential equations in a more robust way than (common) explicit schemes would; threshold equations are smoothed to avoid discontinuities in the model's objective function space; and the model equations are solved simultaneously, avoiding the physically unrealistic sequential solving of fluxes. Generalized parameter ranges are provided to assist with model inter-comparison studies. In addition to this paper and its Supplement, a user manual is provided together with several workflow scripts that show basic example applications of the toolbox. The toolbox and user manual are available from span classCombining double low line"uri"https://github.com/wknoben/MARRMoT/span (last access: 30 May 2019; a hrefCombining double low line"https://doi.org/10.5281/zenodo.3235664"https://doi.org/10.5281/zenodo.3235664). Our main scientific objective in developing this toolbox is to facilitate the inter-comparison of conceptual hydrological model structures which are in widespread use in order to ultimately reduce the uncertainty in model structure selection.
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ItemDevelopment of a Regression Model for Estimating Daily Radiative Forcing Due to Atmospheric Aerosols from Moderate Resolution Imaging Spectrometers (MODIS) Data in the Indo Gangetic Plain (IGP)(MDPI, 2018-10-01)The assessment of direct radiative forcing due to atmospheric aerosols (ADRF) in the Indo Gangetic Plain (IGP), which is a food basket of south Asia, is important for measuring the effect of atmospheric aerosols on the terrestrial ecosystem and for assessing the effect of aerosols on crop production in the region. Existing comprehensive analytical models to estimate ADRF require a large number of input parameters and high processing time. In this context, here, we develop a simple model to estimate daily ADRF at any location on the surface of the IGP through multiple regressions of AErosol RObotic NETwork (AERONET) aerosol optical depth (AOD) and atmospheric water vapour using data from 2002 to 2015 at 10 stations in the IGP. The goodness of fit of the model is indicated by an adjusted R2 value of 0.834. The Jackknife method of deleting one group (station data) was employed to cross validate and study the stability of the regression model. It was found to be robust with an adjusted R2 fluctuating between 0.813 and 0.842. In order to use the year-round ADRF model for locations beyond the AERONET stations in the IGP, AOD, and atmospheric water vapour products from MODIS Aqua and Terra were compared against AERONET station data and they were found to be similar. Using MODIS Aqua and Terra products as input, the year-round ADRF regression was evaluated at the IGP AERONET stations and found to perform well with Pearson correlation coefficients of 0.66 and 0.65, respectively. Using ADRF regression model with MODIS inputs allows for the estimation of ADRF across the IGP for assessing the aerosol impact on ecosystem and crop production.
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ItemSimulating Runoff Under Changing Climatic Conditions: A Framework for Model Improvement(American Geophysical Union, 2018-10-01)Rainfall-runoff models are often deficient under changing climatic conditions, yet almost no recent studies propose new or improved model structures, instead focusing on model intercomparison, input sensitivity, and/or quantification of uncertainty. This paucity of progress in model development is (in part) due to the difficulty of distinguishing which cases of model failure are truly caused by structural inadequacy. Here we propose a new framework to diagnose the salient cause of poor model performance in changing climate conditions, be it structural inadequacy, poor parameterization, or data errors. The framework can be applied to a single catchment, although larger samples of catchments are helpful to generalize and/or cross-check results. To generate a diagnosis, multiple historic periods with contrasting climate are defined, and the limits of model robustness and flexibility are explored over each period separately and for all periods together. Numerous data-based checks also supplement the results. Using a case study catchment from Australia, improved inference of structural failure and clearer evaluation of model structural improvements are demonstrated. This framework enables future studies to (i) identify cases where poor simulations are due to poor calibration methods or data errors, remediating these cases without recourse to structural changes; and (ii) use the remaining cases to gain greater clarity into what structural changes are needed to improve model performance in changing climate.
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ItemNo Preview Available