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

C

• Cao, T.
  • System dynamics applications for defence combat modelling: preliminary insights from a literature exploration
    

    Cunico, G., Elsawah, S., Gary, M.S., Cao, T., Kosowski, L. and Richmond, M.K.
    https://doi.org/10.36334/modsim.2021.M4.cunico

  • Using causal models to evaluate Force Generation options
    

    Shine, D.R., Knoll, J. and Cao, T.
    https://doi.org/10.36334/modsim.2021.M8.shine

  • 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

  • Operational effectiveness of future land combat teams: model conceptualisation
    

    Richmond, M.K., Gary, M.S., Cao, T., Blumson, D., Kosowski, L., Hock, K., Elsawah, S. and Kempt, N.
    https://doi.org/10.36334/modsim.2021.M4.richmond

• Capocchi, L.
  • Discrete event modeling and simulation of smart parking conflict management
    

    Dominici, A., Capocchi, L., De Gentili, E. and Santucci, J-F.
    https://doi.org/10.36334/modsim.2021.E3.dominici

• Cárcamo, N.
  • Bushfire propagation speed: Combining the effects of wind and slope
    

    Berres, S. and Cárcamo, N.
    https://doi.org/10.36334/modsim.2021.G3.berres

• Carlier, R.
  • 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

• Carter, J.
  • Disentangling the effects of management and climate on perennial grass pastures and the degradation that follows multi-year droughts
    

    Owens, J., McKeon, G., O’Reagain, P., Carter, J., Fraser, G., Nelson, B. and Scanlan, J.
    https://doi.org/10.36334/modsim.2021.B1.owens

• Cashen, M.
  • Building responsive bio-economic models to replicate complex farm management decisions for mixed irrigation farming systems in southern NSW
    

    Broadfoot, K., Cashen, M., Behrendt, K., Clark, A.J. and Graham, P.
    https://doi.org/10.36334/modsim.2021.B8.broadfoot

• Castelletti, A.
  • An assessment framework for classifying determinants of household water consumption and their priorities for research and practice
    

    Cominola, A., Preiss, L., Thyer, M., Maier, H.R., Stewart, R. and Castelletti, A.
    https://doi.org/10.36334/modsim.2021.J3.cominola

• Cattle, 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

• Chades, I.
  • Solving constrained K-Markov decision processes
    

    Ferrer-Mestres, J. and Chades, I.
    https://doi.org/10.36334/modsim.2021.I2.ferrermestres

• Chalup, S.
  • Freight train scheduling via decentralised multi-agent deep reinforcement learning
    

    Bretas, A.M.C., Mendes, A., Chalup, S., Jackson, M., Clement, R. and Sanhueza, C.
    https://doi.org/10.36334/modsim.2021.M1.bretas

• Chand, S.S.
  • 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

• Cheema, S.A.
  • Model-based machine learning to explore the nexus between COVID-19 and environmental factors in the United States
    

    Munir, T., Hudson, I.L., Cheema, S.A., Muhammad, R., Shafqat, M. and Kifayat, T.
    https://doi.org/10.36334/modsim.2021.H1.munir

  • 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

• Chiera, B.A.
  • Causality modelling of simulated temporally indexed events to construct a combat narrative
    

    Tiong, J.K.R. and Chiera, B.A.
    https://doi.org/10.36334/modsim.2021.M7.tiong

  • Regression-based approaches for simulation meta-modelling in the presence of heterogeneity and correlation
    

    Garces, L.P.D.M., Bogomolov, T. and Chiera, B.A.
    https://doi.org/10.36334/modsim.2021.M5.garces

• Chow, C.W.K.
  • 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

• Christie, M.J.
  • OneWorld: Evolving an architecture for complex system representation in engagement simulation
    

    Armstrong, R.D., Christie, M.J. and Mellen, P.R.
    https://doi.org/10.36334/modsim.2021.M7.armstrong

  • Comet: A naval Combat Management System model for combat analysis
    

    Blaess, S.G., Christie, M.J. and Mitchell, J.L.
    https://doi.org/10.36334/modsim.2021.M7.blaess

• Chua, C.
  • Developing an Adaptive Evacuation Simulation Framework based on Agent Performance Dynamics
    

    Rollan, T.A., Marquez, L. and Chua, C.
    https://doi.org/10.36334/modsim.2021.G1.rollan

• Clark, A.J.
  • Building responsive bio-economic models to replicate complex farm management decisions for mixed irrigation farming systems in southern NSW
    

    Broadfoot, K., Cashen, M., Behrendt, K., Clark, A.J. and Graham, P.
    https://doi.org/10.36334/modsim.2021.B8.broadfoot

• Clarke, A.R.
  • Does memory help optimise fruit fly foraging at the landscape level?
    

    Newman, J.D., Clarke, A.R., Silva, R. and Parry, H.
    https://doi.org/10.36334/modsim.2021.B7.newman

• Clement, R.
  • Freight train scheduling via decentralised multi-agent deep reinforcement learning
    

    Bretas, A.M.C., Mendes, A., Chalup, S., Jackson, M., Clement, R. and Sanhueza, C.
    https://doi.org/10.36334/modsim.2021.M1.bretas

• Coelli, K.M.
  • 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

• Cohen, R.C.Z.
  • Mechanical digital twinning of the human body in the workplace for reduced injury risk and improved health
    

    Harrison, S.M. and Cohen, R.C.Z.
    https://doi.org/10.36334/modsim.2021.C1.harrison

  • Ergomechanic: A markerless motion capture and ergonomic assessment tool developed using the Workspace workflow engine
    

    Cohen, R.C.Z. and Harrison, S.M.
    https://doi.org/10.36334/modsim.2021.C2.cohen

  • 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

  • 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

  • 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

• Cominola, A.
  • An assessment framework for classifying determinants of household water consumption and their priorities for research and practice
    

    Cominola, A., Preiss, L., Thyer, M., Maier, H.R., Stewart, R. and Castelletti, A.
    https://doi.org/10.36334/modsim.2021.J3.cominola

• Cook, F.J.
  • The use of modelling in design of wastewater subsurface drip irrigation
    

    Cook, F.J., Gearing, P., Bennett, S. and Oakley, R.
    https://doi.org/10.36334/modsim.2021.L2.cook

• Coppola, D.
  • Integrating and automating a closed loop simulation capability to enable easier exploration of the parameter space
    

    Kiparoglou, S. and Coppola, D.
    https://doi.org/10.36334/modsim.2021.M7.kiparoglou

• Coutts, A.
  • Analytic approaches to understanding future Defence workforce needs
    

    Rowe, C., Crockett, A., Rohan-Jones, S., Aljoorfri, S., Tay, N., Coutts, A., Bishop, C., Pay, A., Sim, W., Date, V. and Boyce, J.
    https://doi.org/10.36334/modsim.2021.M8.rowe

  • 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

• Crockett, A.
  • Analytic approaches to understanding future Defence workforce needs
    

    Rowe, C., Crockett, A., Rohan-Jones, S., Aljoorfri, S., Tay, N., Coutts, A., Bishop, C., Pay, A., Sim, W., Date, V. and Boyce, J.
    https://doi.org/10.36334/modsim.2021.M8.rowe

• Croke, B.F.W.
  • 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

• Cuddy, S.M.
  • 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

• Culley, S.A.
  • 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

  • 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

• Cummins, S.J.
  • Extending the capabilities of applications built using the Workspace architecture
    

    Subramanian, R., Thomas, D.G. and Cummins, S.J.
    https://doi.org/10.36334/modsim.2021.C2.subramanian

• Cunico, G.
  • System dynamics applications for defence combat modelling: preliminary insights from a literature exploration
    

    Cunico, G., Elsawah, S., Gary, M.S., Cao, T., Kosowski, L. and Richmond, M.K.
    https://doi.org/10.36334/modsim.2021.M4.cunico

D

• Dandy, G.C.
  • 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

• Daraei, H.
  • 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

• Darnell, R.
  • Opportunistic emulation of computationally expensive simulations via Deep Learning
    

    Sanderson, C., Pagendam, D., Power, B., Bennett, F.R. and Darnell, R.
    https://doi.org/10.36334/modsim.2021.L1.sanderson

• Das, S.
  • Geostatistical merging of weather radar data with a sparse rain gauge network in Queensland
    

    Sharp, C., Schepen, A., Das, S. and Everingham, Y.
    https://doi.org/10.36334/modsim.2021.K6.sharp

• Date, V.
  • Analytic approaches to understanding future Defence workforce needs
    

    Rowe, C., Crockett, A., Rohan-Jones, S., Aljoorfri, S., Tay, N., Coutts, A., Bishop, C., Pay, A., Sim, W., Date, V. and Boyce, J.
    https://doi.org/10.36334/modsim.2021.M8.rowe

• Dawson, C.W.
  • 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

• Dayananda, M.D.T.
  • 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

• De Gentili, E.
  • Discrete event modeling and simulation of smart parking conflict management
    

    Dominici, A., Capocchi, L., De Gentili, E. and Santucci, J-F.
    https://doi.org/10.36334/modsim.2021.E3.dominici

• de la Torre-Sanzana, M.
  • Algorithms for diffusion and convection models implemented using open source libraries
    

    Mas-Hernandez, E., Mancilla-Barría, E.A., de la Torre-Sanzana, M. and Berres, S.
    https://doi.org/10.36334/modsim.2021.C3.mas-hernandez

• Dekker, A.
  • Understanding Eurovision tele-voting through modelling
    

    Dekker, A.
    https://doi.org/10.36334/modsim.2021.I8.dekker2

  • ‘Him makeum walk straight’: using simulation to explore Australian Aboriginal skin groups
    

    Dekker, A.
    https://doi.org/10.36334/modsim.2021.I8.dekker

• Demirhan, H.
  • Factor screening for binary responses from combat simulations
    

    Demirhan, H., Georgiou, S., Gill, A. and Stylianou, S.
    https://doi.org/10.36334/modsim.2021.M5.demirhan

• Deng, C.
  • 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

• Deo, A.
  • 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

• Dilhari, W.A.D.S.
  • 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

• Doherty, J.
  • Estimating rainfall-runoff model parameters using the iterative ensemble smoother
    

    Bennett, F.R. and Doherty, J.
    https://doi.org/10.36334/modsim.2021.L1.bennett

• Dominici, A.
  • Discrete event modeling and simulation of smart parking conflict management
    

    Dominici, A., Capocchi, L., De Gentili, E. and Santucci, J-F.
    https://doi.org/10.36334/modsim.2021.E3.dominici

• Donaghy, D.J.
  • Preliminary results of parameterisation of DairyMod pasture model for tropical pasture; Brachiaria
    

    Jayasinghe, J.M.P., Donaghy, D.J., Pembleton, K.G., Barber, D.G. and Ramilan, T.
    https://doi.org/10.36334/modsim.2021.B1.jayasinghe

• Donnelly, C.
  • 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

• Donohoo, A.
  • Command Professional Edition: Initial insights of a commercial military operational modelling and simulation tool
    

    Hagley, S., Lo, E.H.S., Hoek, P.J., Donohoo, A. and Peacock, J.
    https://doi.org/10.36334/modsim.2021.M7.hagley

• Dowdy, A.J.
  • 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

• Duan, 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

• Duarte, S.N.
  • 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