Author Index

* Please note this includes full papers only

A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z

U

• Ugbaje, S.
  • A nationally scalable approach to simulating soil organic carbon in agricultural landscapes
    

    Coelli, K.M., Karunaratne, S.B., Baldock, J.A., Ugbaje, S., Buzacott, A.J.V., Filippi, P., Cattle, S. and Bishop, T.F.A.
    https://doi.org/10.36334/modsim.2021.B6.coelli

• Ugon, J.
  • Hydrogen bus route planning in regional Victoria
    

    Esmaeilbeigi, R., Mak-Hau, V., Pineda-Villavicencio, G. and Ugon, J.
    https://doi.org/10.36334/modsim.2021.M1.esmaeilbeigi

• Ullah, K.
  • Use of auxiliary information in estimation of the finite population mean: An exponential type of estimator
    

    Ullah, K., Hudson, I.L., Cheema, S.A., Khan, A., Rahman, A.R. and Hussian, Z.
    https://doi.org/10.36334/modsim.2021.A1.ullah

• Urich, C.
  • The local influence of residential infill on the urban water flows: a multi-city analysis
    

    Moravej, M., Kenway, S., Renouf, M., Urich, C., Sainsbury, O., Bertram, N. and London, G.
    https://doi.org/10.36334/modsim.2021.J4.moravej

V

• van Delden, H.
  • Uncertainty, sensitivity and scenario analysis: how do they fit together?
    

    Maier, H.R., Guillaume, J.H.A., McPhail, C., Westra, S., Kwakkel, J.H., Razavi, S., van Delden, H., Thyer, M.A., Culley, S.A. and Jakeman, A.J.
    https://doi.org/10.36334/modsim.2021.J5.maier

  • Modelling future changes in social vulnerability and bushfire risk
    

    Moore, E., Zhar, Y., Radford, P., O'Callaghan, M., Maier, H.R., Riddell, G., van Delden, H. and Wouters, M.
    https://doi.org/10.36334/modsim.2021.G1.moore

• Van Der Linden, L.
  • Water security analysis of the Middle River supply system: a foreSIGHT application
    

    Culley, S., Westra, S., Bennett, B., Maier, H.R., Newman, J., Van Der Linden, L. and Irvine, M.
    https://doi.org/10.36334/modsim.2021.J5.culley

• van der Sterren, M.
  • Lessons learned using dSedNet plug-in within a water supply catchment for Greater Sydney
    

    Amini, S., Pont, J., van der Sterren, M. and Freebairn, A.
    https://doi.org/10.36334/modsim.2021.F7.amini

• van der Velde, M.
  • Trade strategies to mitigate the global impact of regional wheat production shocks
    

    Golding, P., Kapadia, S., Naylor, S., Schulz, J., Maier, H.R., Lall, U. and van der Velde, M.
    https://doi.org/10.36334/modsim.2021.B5.golding

• Van Hooff, M.
  • The role of embodied cognition in linguistic mental health analysis
    

    Kernot, D., Van Hooff, M., Lawrence-Wood, E., Glenny, L., Snowden, C., Green, K. and Son, C.
    https://doi.org/10.36334/modsim.2021.H2.kernot

• van Leeuwen, J.
  • A model based on DOC data for determination of alum dosing for drinking water treatment
    

    Daraei, H., Awad, J., Bertone, E., Stewart, R.A., Chow, C.W.K., Duan, J. and van Leeuwen, J.
    https://doi.org/10.36334/modsim.2021.L2.daraei

• Verburg, K.
  • Considering unknown uncertainty in imperfect models: nitrogen mineralization as a case study
    

    Vilas, M.P., Bennett, F.R., Verburg, K. and Adams, M.P.
    https://doi.org/10.36334/modsim.2021.B3.vilas

• Vilas, M.P.
  • Modelling to determine key drivers of water quality off sugarcane paddocks in the Great Barrier Reef catchment
    

    Power, B., Shaw, M., Vilas, M.P., Farr, M. and Thompson, M.
    https://doi.org/10.36334/modsim.2021.L1.power

  • Considering unknown uncertainty in imperfect models: nitrogen mineralization as a case study
    

    Vilas, M.P., Bennett, F.R., Verburg, K. and Adams, M.P.
    https://doi.org/10.36334/modsim.2021.B3.vilas

• Vogel, E.
  • Estimation of road closure risks along the Bruce highway using the AWRA-L water balance model
    

    Vogel, E., Lerat, J., Gericke, L.A., Russell, C.A., Preece, A., Stuart, G., Pipunic, R., Khan, Z. and Donnelly, C.
    https://doi.org/10.36334/modsim.2021.K5.vogel

W

• Wadhwani, R.
  • Improvement of drag model for non-burning firebrand transport in Fire Dynamics Simulator
    

    Wadhwani, R., Sutherland, D., Thorpe, G. and Moinuddin, K.A.
    https://doi.org/10.36334/modsim.2021.G3.wadhwani

  • Application of neural networks to rate of spread estimation in shrublands
    

    Wadhwani, R., Sutherland, D., Moinuddin, K.A. and Sharples, J.J.
    https://doi.org/10.36334/modsim.2021.G3.wadhwani2

• Wark, S.
  • Evaluating instruction quality across narrative modality using measures of real-time cognitive load
    

    Smith, S.P., Blackmore, K., Wark, S. and Nowina-Krowicki, M.
    https://doi.org/10.36334/modsim.2021.M2.smith

• Warren, R.
  • Enhancement of lightning strike forecasts using a machine learning approach
    

    Gow, D., Lerat, J., Warren, R. and Blockley, I.
    https://doi.org/10.36334/modsim.2021.K7.gow

• Watkins, D.
  • Implementing a fully homomorphic encrypted circuit in Workspace
    

    Nguyen, D. and Watkins, D.
    https://doi.org/10.36334/modsim.2021.C2.nguyen

  • Using Workspace to implement Digital Twins in the Mixed Reality Lab
    

    Watkins, D., Bolger, M., Hetherton, L., Zhang, Z., Xie, P., Harrison, S.M. and Cohen, R.C.Z.
    https://doi.org/10.36334/modsim.2021.C1.watkins

• Watt, S.
  • Application of a delayed logistic equation to a reindeer population in a closed environment
    

    Watt, S., Jovanoski, Z., Towers, I., Saifuddin, R. and Sidhu, H.
    https://doi.org/10.36334/modsim.2021.F3.watt

  • Stochastic modelling of wind and its implication for wildfire spread predictions
    

    Masoudian, S., Sharples, J.J., Jovanoski, Z., Towers, I. and Watt, S.
    https://doi.org/10.36334/modsim.2021.G3.masoudian

  • Modelling of a five reactor Activated Sludge cascade process using ASM #1
    

    Watt, S., Nelson, M., Hai, F. and Sidhu, H.
    https://doi.org/10.36334/modsim.2021.L2.watt

  • The population dynamics of ecosystem engineers and habitat modification
    

    Watt, S., Jovanoski, Z., Towers, I., Saifuddin, R. and Sidhu, H.
    https://doi.org/10.36334/modsim.2021.F3.watt2

• Waud, M.W.
  • Assessing performance of the MERGE model for simulating gully interventions
    

    Prentice, M.J., Waud, M.W., Hamilton, D.P. and Roberts, M.E.
    https://doi.org/10.36334/modsim.2021.L4.prentice

• Weerahewa, J.
  • An assessment of economic and environmental benefits of desilting village tanks in Sri Lanka: An application of linear programming
    

    Dayananda, M.D.T., Dilhari, W.A.D.S. and Weerahewa, J.
    https://doi.org/10.36334/modsim.2021.J7.dayananda

  • Economically optimum N fertiliser decisions for rice cultivation in Sri Lanka: Does soil type matter?
    

    Kanthilanka, H., Farquharson, R.J., Ramilan, T. and Weerahewa, J.
    https://doi.org/10.36334/modsim.2021.B5.kanthilanka

• Weeraratne, V.C.N.
  • Coastal inundation modelling and adaptation assessment for the Bellarine Peninsula
    

    Weeraratne, V.C.N., Cohen, R.C.Z., Roob, R. and Prakash, M.
    https://doi.org/10.36334/modsim.2021.G1.weeraratne2

  • INDRA – Climate Resilience Platform for the City of Makassar
    

    Weeraratne, V.C.N., Prakash, M., Cohen, R.C.Z. and Garg, N.
    https://doi.org/10.36334/modsim.2021.G1.weeraratne

• Weinberg, G.V.
  • Determining performance limits for directed energy weapons in collaborative active protections systems
    

    Weinberg, G.V.
    https://doi.org/10.36334/modsim.2021.M7.weinberg2

  • A queueing theoretic approach for performance prediction of collaborative active protection systems
    

    Weinberg, G.V.
    https://doi.org/10.36334/modsim.2021.M7.weinberg

• Weligamage, H.A.C.G.
  • Observation based gridded annual runoff estimates over Victoria, Australia
    

    Weligamage, H.A.C.G., Fowler, K.J.A., Peterson, T.J., Saft, M. and Peel, M.C.
    https://doi.org/10.36334/modsim.2021.K11.weligamage

• Wen, L.
  • Assessing waterbird breeding conditions using an emulator of wetland inundation regime
    

    Quijano, J., Rodriguez, J., Kuczera, G., Saco, P.M., Sandi, S.G., Carlier, R., Wen, L. and McDonough, K.
    https://doi.org/10.36334/modsim.2021.J1.quijano

• Western, A.W.
  • An automatic system to estimate crop phenological dates with remote sensing: A case study in the southeast Australia
    

    Gao, Z., Guo, D., Ryu, D. and Western, A.W.
    https://doi.org/10.36334/modsim.2021.K6.gao

• Westra, S.
  • Water security analysis of the Middle River supply system: a foreSIGHT application
    

    Culley, S., Westra, S., Bennett, B., Maier, H.R., Newman, J., Van Der Linden, L. and Irvine, M.
    https://doi.org/10.36334/modsim.2021.J5.culley

  • Modelling hydrological change due to wildfires
    

    Partington, D., Thyer, M., Shanafield, M., McInerney, D., Westra, S., Maier, H.R., Simmons, C.T., Croke, B.F.W., Jakeman, A.J., Gupta, H.V. and Kavetski, D.
    https://doi.org/10.36334/modsim.2021.J8.partington

  • Uncertainty, sensitivity and scenario analysis: how do they fit together?
    

    Maier, H.R., Guillaume, J.H.A., McPhail, C., Westra, S., Kwakkel, J.H., Razavi, S., van Delden, H., Thyer, M.A., Culley, S.A. and Jakeman, A.J.
    https://doi.org/10.36334/modsim.2021.J5.maier

• Wheat, D.
  • The Open Maritime Traffic Analysis Dataset
    

    Masek, M., Lam, C.P., Rybicki, T., Snell, J., Wheat, D., Kelly, L., Glassborow, D. and Smith-Gander, C.
    https://doi.org/10.36334/modsim.2021.M9.masek

• Wiedmann, T.
  • An inclusive city water account by integrating multiple data sources for South-East Queensland (SEQ), Australia
    

    Islam, K.M.N., Kenway, S.J., Renouf, M.A. and Wiedmann, T.
    https://doi.org/10.36334/modsim.2021.J7.islam

• Wilson, P.
  • Towards a provenance-enabled, reproducible, and extensible machine learning platform by integrating databases, web services, containers, and code repositories in a loosely coupled manner
    

    Singh, R.M., Wilson, P., Gregory, L., Seaton, S. and Malone, B.
    https://doi.org/10.36334/modsim.2021.C4.singh

• Withers, K.R.
  • The closed loop military maintenance workforce: A simulation-based optimisation approach
    

    Withers, K.R., Turan, H.H., Kahagalage, S. and Elsawah, S.
    https://doi.org/10.36334/modsim.2021.M2.withers

• Woldemeskel, F.
  • Advances in subseasonal streamflow forecasting: An overview
    

    Thyer, M., McInerney, D., Kavetski, D., Laugesen, R., Woldemeskel, F., Tuteja, N. and Kuczera, G.
    https://doi.org/10.36334/modsim.2021.K5.thyer

  • Improving sub-seasonal streamflow forecasts across flow regimes
    

    McInerney, D., Thyer, M., Kavetski, D., Laugesen, R., Woldemeskel, F., Tuteja, N. and Kuczera, G.
    https://doi.org/10.36334/modsim.2021.K5.mcinerney

• Wouters, M.
  • Modelling future changes in social vulnerability and bushfire risk
    

    Moore, E., Zhar, Y., Radford, P., O'Callaghan, M., Maier, H.R., Riddell, G., van Delden, H. and Wouters, M.
    https://doi.org/10.36334/modsim.2021.G1.moore

• Wu, W.
  • A framework for engaging stakeholders in solving real-world water resources management problems
    

    Wu, W., Maier, H.R., Dandy, G.C., Leonard, R., Bellette, K., Cuddy, S.M. and Maheepala, S.
    https://doi.org/10.36334/modsim.2021.F3.wu

  • Beyond validation: assessing the legitimacy of artificial neural network models
    

    Humphrey, G.B., Maier, H.R., Wu, W., Mount, N.J., Dandy, G.C. and Dawson, C.W.
    https://doi.org/10.36334/modsim.2021.A3.humphrey

X

• Xie, P.
  • Using Workspace to implement Digital Twins in the Mixed Reality Lab
    

    Watkins, D., Bolger, M., Hetherton, L., Zhang, Z., Xie, P., Harrison, S.M. and Cohen, R.C.Z.
    https://doi.org/10.36334/modsim.2021.C1.watkins

Y

• Yao, H.
  • Estimating tail probabilities of random sums of scale mixture of phase-type random variables
    

    Yao, H. and Taimre, T.
    https://doi.org/10.36334/modsim.2021.A1.yao

• Ye, H.
  • Tropical cyclone-induced extreme winds in climate datasets: East coast of Australia
    

    Bell, S.S., Chand, S.S., Dowdy, A.J., Ramsay, H.A., Deo, A., Su, C.-H., Brown, A. and Ye, H.
    https://doi.org/10.36334/modsim.2021.G4.bell

  • Extreme bushfire projections using a standardised method
    

    Dowdy, A.J., Thatcher, M., Rafter, T., Evans, J., Ye, H., Su, C.-H., Stassen, C., Pepler, A., Bell, S.S. and Steinle, P.
    https://doi.org/10.36334/modsim.2021.G3.dowdy

• Ye, N.
  • MOOR: Model-based Offline Reinforcement learning for sustainable fishery management
    

    Ju, J., Kurniawati, H., Kroese, D. and Ye, N.
    https://doi.org/10.36334/modsim.2021.M2.ju

  • Prior versus data: A new Bayesian method for fishery stock assessment
    

    Lei, Y., Zhou, S. and Ye, N.
    https://doi.org/10.36334/modsim.2021.A1.lei

• Yearwood, J.
  • A regret-based incremental elicitation for multi-criteria force design
    

    Mak-Hau, V., Cao, T. and Yearwood, J.
    https://doi.org/10.36334/modsim.2021.M8.mak-hau

• Young, J.
  • CFD solver validations for simulating passively pitching tandem wings in hovering flight
    

    Huang, Q., Mazharmanesh, S., Tian, F.-B., Young, J., Lai, J.C.S. and Ravi, S.
    https://doi.org/10.36334/modsim.2021.A2.huang

• Yu, Y.
  • Continental scale downscaling of AWRA-L analysed soil moisture using random forest regression
    

    Yu, Y., Renzullo, L.J. and Tian, S.
    https://doi.org/10.36334/modsim.2021.J10.yu

Z

• Zhang, H.
  • Temporal convolutional network algorithm for streamflow predictions in a subtropical river
    

    Liu, Y.L., Deng, C. and Zhang, H.
    https://doi.org/10.36334/modsim.2021.J13.liu

• Zhang, L.
  • A large-scale multi-rider matching problem with reneging passengers: single source case
    

    Fu, J., Zhang, L., Huang, K. and Liu, Z.
    https://doi.org/10.36334/modsim.2021.M3.fu

  • Assessing last mile delivery strategies – A hybrid solution approach
    

    Muriel, J.E., Zhang, L., Fransoo, J.C. and Perez-Franco, R.
    https://doi.org/10.36334/modsim.2021.M1.muriel

• Zhang, Z.
  • Using Workspace to implement Digital Twins in the Mixed Reality Lab
    

    Watkins, D., Bolger, M., Hetherton, L., Zhang, Z., Xie, P., Harrison, S.M. and Cohen, R.C.Z.
    https://doi.org/10.36334/modsim.2021.C1.watkins

• Zhar, Y.
  • Modelling future changes in social vulnerability and bushfire risk
    

    Moore, E., Zhar, Y., Radford, P., O'Callaghan, M., Maier, H.R., Riddell, G., van Delden, H. and Wouters, M.
    https://doi.org/10.36334/modsim.2021.G1.moore

• Zhou, S.
  • Prior versus data: A new Bayesian method for fishery stock assessment
    

    Lei, Y., Zhou, S. and Ye, N.
    https://doi.org/10.36334/modsim.2021.A1.lei

• Zuffo, A.C.
  • Evaluation of the time of concentration estimation methods for small rural watersheds
    

    Rezende, B.N., Boulomytis, V.T.G., Duarte, S.N., Jacomazzi, M.A. and Zuffo, A.C.
    https://doi.org/10.36334/modsim.2021.J7.rezende

• Zuparic, M.
  • An evaluation model and tool for Defence capability options
    

    Nguyen, M.-T., Coutts, A., Knoll, J., Zuparic, M., Peacock, J., Bilusich, D., Galister, M. and Johns, K.
    https://doi.org/10.36334/modsim.2021.M8.nguyen