ORCID Profile
0000-0003-2494-0518
Current Organisation
Australian National University
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Publisher: Elsevier BV
Date: 2010
Publisher: American Geophysical Union (AGU)
Date: 11-2020
DOI: 10.1029/2020WR027721
Publisher: Royal Society of Chemistry (RSC)
Date: 2021
DOI: 10.1039/D1TC03606H
Abstract: Selective chemiresistive gas sensing using metal–organic framework encapsulated ultra-porous metal oxide nanoparticle network.
Publisher: Springer International Publishing
Date: 2014
Publisher: Elsevier BV
Date: 10-2014
Publisher: Elsevier BV
Date: 08-2019
Publisher: Elsevier BV
Date: 06-2019
Publisher: Elsevier BV
Date: 2017
Publisher: Elsevier BV
Date: 04-2019
Publisher: Elsevier BV
Date: 05-2009
Publisher: Elsevier BV
Date: 07-2015
DOI: 10.1016/J.JENVMAN.2015.04.021
Abstract: Globally wetlands are increasingly under threat due to changes in water regimes as a result of river regulation and climate change. We developed the Exploring CLimAte Impacts on Management (EXCLAIM) decision support system (DSS), which simulates flow-driven habitat condition for 16 vegetation species, 13 waterbird species and 4 fish groups in the Macquarie catchment, Australia. The EXCLAIM DSS estimates impacts to habitat condition, considering scenarios of climate change and water management. The model framework underlying the DSS is a probabilistic Bayesian network, and this approach was chosen to explicitly represent uncertainties in climate change scenarios and predicted ecological outcomes. The results suggest that the scenario with no climate change and no water resource development (i.e. flow condition without dams, weirs or water license entitlements, often regarded as a surrogate for 'natural' flow) consistently has the most beneficial outcomes for vegetation, waterbird and native fish. The 2030 dry climate change scenario delivers the poorest ecological outcomes overall, whereas the 2030 wet climate change scenario has beneficial outcomes for waterbird breeding, but delivers poor outcomes for river red gum and black box woodlands, and fish that prefer river channels as habitats. A formal evaluation of the waterbird breeding model showed that higher numbers of observed nest counts are typically associated with higher modelled average breeding habitat conditions. The EXCLAIM DSS provides a generic framework to link hydrology and ecological habitats for a large number of species, based on best available knowledge of their flood requirements. It is a starting point towards developing an integrated tool for assessing climate change impacts on wetland ecosystems.
Publisher: American Geophysical Union (AGU)
Date: 08-2023
DOI: 10.1029/2022WR032194
Abstract: Factor Fixing (FF) is a common method for reducing the number of model parameters to lower computational cost. FF typically starts with distinguishing the insensitive parameters from the sensitive and pursues uncertainty quantification (UQ) on the resulting reduced‐order model, fixing each insensitive parameter at a fixed value. There is a need, however, to expand such a common approach to consider the effects of decision choices in the FF‐UQ procedure on metrics of interest. Therefore, to guide the use of FF and increase confidence in the resulting dimension‐reduced model, we propose a new adaptive framework consisting of four principles: (a) re‐parameterize the model first to reduce obvious non‐identifiable parameter combinations, (b) focus on decision relevance especially with respect to errors in quantities of interest (QoI), (c) conduct adaptive evaluation and robustness assessment of errors in the QoI across FF choices as s le size increases, and (d) reconsider whether fixing is warranted. The framework is demonstrated on a spatially‐distributed water quality model. The error in estimates of QoI caused by FF can be estimated using a Polynomial Chaos Expansion (PCE) surrogate model. Built with 70 model runs, the surrogate is computationally inexpensive to evaluate and can provide global sensitivity indices for free. For the selected catchment, just two factors may provide an acceptably accurate estimate of model uncertainty in the average annual load of Total Suspended Solids (TSS), suggesting that reducing the uncertainty in these two parameters is a priority for future work before undertaking further formal uncertainty quantification.
Publisher: Elsevier BV
Date: 08-2020
Publisher: Elsevier BV
Date: 10-2013
DOI: 10.1016/J.JENVMAN.2013.05.005
Abstract: Sediment monitoring, tracing and modelling are widely used to identify suspended sediment sources. Although each method has inherent limitations and uncertainties, their integration provides opportunities to form collective knowledge and encourages robust management strategies. This paper presents a Weight-of-Evidence approach to integrate multiple Lines-of-Evidence for identifying suspended sediment sources. Three sources of evidence were used: i) stream flow and suspended sediment monitoring at river gauges ii) geochemical sediment tracing at river junctions and iii) catchment-scale suspended sediment modelling of hillslope, gully, streambank and unsealed road erosion. We applied this approach on two data-poor catchments in Australia. Some reaches were consistently identified as major sources of sediment from all Lines-of-Evidence. However, inconsistencies between the types of evidence in other areas highlighted the high uncertainty in identifying suspended sediment sources in these areas and the need for further investigation. The integration framework maximised the use of scarce information, enabled explicit consideration of uncertainties for catchment management and identified where future monitoring and research should be targeted.
Publisher: Elsevier BV
Date: 09-2015
Publisher: Copernicus GmbH
Date: 05-06-2018
Abstract: Abstract. Management of water resources requires understanding of the hydrology and hydrogeology, as well as the policy and human drivers and their impacts. This understanding requires relevant inputs from a wide range of disciplines, which will vary depending on the specific case study. One approach to gain understanding of the impact of climate and society on water resources is through the use of an integrated modelling process that engages stakeholders and experts in specifics of problem framing, co-design of the underpinning conceptual model, and discussion of the ensuing results. In this study, we have developed such an integrated modelling process for the C aspe basin in northern Victoria, Australia. The numerical model built has a number of components: Node/link based surface water hydrology module based on the IHACRES rainfall-streamflow model Distributed groundwater model for the lower catchment (MODFLOW) Farm decision optimisation module (to determine irrigation requirements) Policy module (setting conditions on availability of water based on existing rules) Ecology module (determining the impacts of available streamflow on platypus, fish and river red gum trees) The integrated model is component based and has been developed in Python, with the MODFLOW and surface water hydrology model run in external programs, controlled by the master program (in Python). The integrated model has been calibrated using historical data, with the intention of exploring the impact of various scenarios (future climate scenarios, different policy options, water management options) on the water resources. The scenarios were selected based on workshops with, and a social survey of, stakeholders in the basin regarding what would be socially acceptable and physically plausible options for changes in management. An ex le of such a change is the introduction of a managed aquifer recharge system to capture dam overflows, and store at least a portion of this in the aquifer, thereby increasing the groundwater resource as well as reducing the impact of existing pumping levels.
No related grants have been discovered for Baihua Fu.