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Author Index

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, H.T.
    • Modelling the impacts of non-kinetic factors on combat effectiveness: The role of deception
      Hock, K., Staby, S.-E., Gary, M.S., Kosowski, L., Blumson, D., Cao, H.T., Elsawah, S., Kempt, N. and Richmond, M.K.
      https://doi.org/10.36334/modsim.2023.hock
  • Cao, Y.J.
    • Agricultural resilience to a severe drought in the Yangtze River Basin, China
      Cao, Y.J. and Zhang, Y.Q.
      https://doi.org/10.36334/modsim.2023.cao
    • Impacts of a severe drought on vegetation and hydrological systems in the Yangtze River Basin, China
      Zhang, Y.Q., Tian, J., Zhang, X.Z., Ma, N., Tang, Z.X., Kong, D.D., Cao, Y.J., Shao, X.M., Wei, H.S., Chen, Y.Y., Wang, J., Wang, L.H., Xu, Z.W., Li, C.C., Yang, X.N. and Ren, C.Y.
      https://doi.org/10.36334/modsim.2023.zhang223
  • Carey, B.
    • Strategic assessment of proposed river infrastructure, with Clarence River – Bellingen Pipeline, as an example
      Driver, P.D., Taylor, N., Carey, B., Cu, T.P., Brookes, K. and Harris, D.
      https://doi.org/10.36334/modsim.2023.driver209
  • Carey, C.C.
    • Temporal variability of phytoplankton community structure: An individual-based modelling approach
      Ranjbar, M.H., Hamilton, D.P., Pace, M.L., Etemad-Shahidi, A., Carey, C.C. and Helfer, F.
      https://doi.org/10.36334/modsim.2023.ranjbar
  • Carlier, R.
    • An ecohydrological approach for modelling and optimisation of vegetation health in dryland wetlands
      Rodríguez, J.F., Saco, P.M., Sandi, S.G., Quijano Baron, J.P., Carlier, R., Kuczera, G. and Wen, L.
      https://doi.org/10.36334/modsim.2023.rodriguez
  • Carrara, E.
    • Adapting JULES for improved hydrological predictions in Australia: Challenges, strategies and future plans
      Tian, S., Rüdiger, C., Renzullo, L.J., Dharssi, I., Marchionni, V., Woldemeskel, F., Frost, A. and Carrara, E.
      https://doi.org/10.36334/modsim.2023.tian575
    • Towards a seamless probabilistic flood inundation modelling capability across the disaster response timeline
      Hou, J., Sharples, W., Bahramian, K., Pickett-Heaps, C.A., Woldemeskel, F., Rüdiger, C. and Carrara, E.
      https://doi.org/10.36334/modsim.2023.hou353
  • Carter, J.
  • Cassey, P.
    • Modelling eradication potential of a newly developed gene drive strategy in mice using spatially explicit agent-based simulations
      Birand, A., Gierus, L., Cassey, P., Ross, J.V., Prowse, T.A.A. and Thomas, P.Q.
      https://doi.org/10.36334/modsim.2023.birand
  • Castellazzi, P.
    • Mapping groundwater-dependent ecosystems using a phenology matrix and fine-scale remote sensing data
      Gao, S., Castellazzi, P., Pritchard, J.L., Stratford, D. and Doody, T.M.
      https://doi.org/10.36334/modsim.2023.gao605
  • Celestina, C.
    • Prediction of wheat and barley phenology through integration of genomic prediction and a crop growth model
      Zheng, B., Brown, H., Zhao, Z.G., Wang, E., Huth, N.I., Dillon, S., Hyles, J., Rathjen, T., Bloomfield, M., Celestina, C., Hunt, J. and Trevaskis, B.
      https://doi.org/10.36334/modsim.2023.zheng289
  • Chadès, I.
    • Planning research and development in poor data and urgent decision-making contexts as an adaptive management problem
      Pascal, L.V., Adams, M.P., Chadès, I. and Helmstedt, K.J.
      https://doi.org/10.36334/modsim.2023.pascal
  • Chambel Leitão, P.
    • WaterSENSE: Update on implementing water use monitoring and assessment services
      Wonink, S., Jackson, B., Brombacher, J., Vervoort, R.W., Einfalt, T., Anderlieste, M., Chambel Leitão, P. and Noort, M.
      https://doi.org/10.36334/modsim.2023.wonink
  • Chapman, G.
    • Estimating sediment delivery ratios using connectivity index and high-resolution digital elevation model at lower Snowy River area, Australia
      Yang, X., Young, J., Shi, H., Chapman, G., Pulsford, I., Moore, C., Gormley, A. and Thackway, R.
      https://doi.org/10.36334/modsim.2023.yang112
  • Chapman, S.
    • A snapshot of climate change impacts for Queensland and regions using high-resolution downscaled CMIP6 projections
      Toombs, N., Chapman, S., Trancoso, R., Zhang, H., Owens, D. and Syktus, J.
      https://doi.org/10.36334/modsim.2023.toombs
    • Assessing the impact of bias correction approaches on climate extremes and the climate change signal
      Zhang, H., Chapman, S., Trancoso, R., Toombs, N. and Syktus, J.
      https://doi.org/10.36334/modsim.2023.zhang49
    • The impact of bias correction on reference evapotranspiration and its climate change signal
      Zhang, H., Chapman, S., Trancoso, R., Toombs, N. and Syktus, J.
      https://doi.org/10.36334/modsim.2023.zhang48
    • Maximizing wheat grain yield in irrigated mega-environments: Targeting optimal flowering period by selecting optimal sowing date and genotype with appropriate phenological development pattern
      Hu, P., Zheng, B. and Chapman, S.
      https://doi.org/10.36334/modsim.2023.hu675
  • Chaweewongpaisal, M.
    • Area-business continuity management web application model test plan
      Tang, J., Leelawat, N., Sornklin, B., Chaweewongpaisal, M., Vikraipaisarn, Y., Bhisitcharoentat, Y., Arayachookiat, P., Meechang, K., Kodaka, A., Iwasaki, Y., Inoue, M. and Watanabe, K.
      https://doi.org/10.36334/modsim.2023.tang226
  • Chen, F.
    • Improving the performance of vertical slotted breakwater and modeling its hydrodynamic behavior by genetic programming
      Gandomi, M., Khorshidi, M.S., Reza Nikoo, M., Chen, F. and Gandomi, A.H.
      https://doi.org/10.36334/modsim.2023.gandomi
    • Enhancing empirical modelling in environmental science with knowledge discovery and genetic programming
      Khorshidi, M.S., Gandomi, M., Reza Nikoo, M., Yazdani, D., Chen, F. and Gandomi, A.H.
      https://doi.org/10.36334/modsim.2023.khorshidi
  • Chen, N.
  • Chen, Y.Y.
    • Impacts of a severe drought on vegetation and hydrological systems in the Yangtze River Basin, China
      Zhang, Y.Q., Tian, J., Zhang, X.Z., Ma, N., Tang, Z.X., Kong, D.D., Cao, Y.J., Shao, X.M., Wei, H.S., Chen, Y.Y., Wang, J., Wang, L.H., Xu, Z.W., Li, C.C., Yang, X.N. and Ren, C.Y.
      https://doi.org/10.36334/modsim.2023.zhang223
  • Cheng, L.
  • Cherukuru, N.
    • Mapping water quality in complex estuarine and coastal waters using deep learning models and high-resolution satellite imagery
      Unnithan, S.L.K., Cherukuru, N., Drayson, N. and Ingleton, T.
      https://doi.org/10.36334/modsim.2023.unnithan
    • Application of denoising diffusion models in the augmentation of a regional dataset of inherent optical properties and applications for remote sensing
      Drayson, N., Diakogiannis, F., Cherukuru, N., Blondeau-Patissier, D. and Schroeder, T.
      https://doi.org/10.36334/modsim.2023.drayson
  • Chin, B.
  • Choudhury, D.
    • A new Python module to convert WRF regional climate projections into CORDEX-compliant datasets
      Tam, E., Di Virgilio, G., Vieira Rocha, C., Choudhury, D., Ji, F., Hannah, N. and Riley, M.
      https://doi.org/10.36334/modsim.2023.tam
  • Clemens, R.
  • Cleverly, J.
    • From modelling to measurements: Bridging gaps in modelling with measured vegetation, evapotranspiration and soil moisture data
      Owens, J., Cleverly, J., Hutley, L.B., Frost, A. and Western, A.W.
      https://doi.org/10.36334/modsim.2023.owens
  • Cobban, D.
    • Identifying groundwater-dependent vegetation in arid zone Australia using imagery time series and singular value decomposition
      Box, P., Brim Box, J., Cobban, D., Lieper, I. and Nano, C.
      https://doi.org/10.36334/modsim.2023.box387
  • Collins, B.
    • i-RAT: An interactive rapid assessment tool to assess economic and environmental impacts of different sugarcane irrigation practices
      Collins, B., Attard, S., Banhalmi-Zakar, Z. and Everingham, Y.
      https://doi.org/10.36334/modsim.2023.collins
  • Cook, A.
    • Trends in brain injury among United States female students linked to consumer products
      Le, T.D., Cook, A., Keyloun, J.W., Ledlow, G., Pusateri, A.E., Uhm, M., Bae, S. and Singh, K.P.
      https://doi.org/10.36334/modsim.2023.le254
  • Cook, E.R.
  • Cook, P.
    • Identifying and quantifying key sources of nutrient pollution from irrigated agriculture
      Sargent, R., Henry, R., Wong, W.W., Schang, C., Tseng, C.W., Cook, P., Western, A.W., McCarthy, D. and Lintern, A.
      https://doi.org/10.36334/modsim.2023.sargent
  • Cookson, A.L.
    • Net export of E. coli from the Toenepi wetland cannot be explained by growth of naturalized E. coli in the water column
      Muirhead, R.W., Stott, R., Sukias, J.P.S., Devane, M. and Cookson, A.L.
      https://doi.org/10.36334/modsim.2023.muirhead
  • Cornish, A.
    • From surface runoff to streamflow: An application of statistical post-processing for seasonal streamflow forecasting
      Pickett-Heaps, C.A., Sunter, P., Cornish, A., Sharples, W., Pegios, M. and Wilson, C.
      https://doi.org/10.36334/modsim.2023.pickettheaps
  • Crépin, A.S.
    • A review of quantitative resilience measurements: Gaps in the operationalisation of agency and diversity in resilience metrics
      Sanches, V.H., Crépin, A.S., Dakos, V., Donges, J.F., Guillaume, J.H.A., Haider, J.L., Iwanaga, T., Kwakkel, J.H., Lade, S.J., Quinlan, A.E., Quiñones, R., Rocha, J.C. and Vivas, J.
      https://doi.org/10.36334/modsim.2023.sanches
  • Cresswell, A.
    • Connectivity modelling at local scales identifies sources and sinks of coral recruitment within reef clusters
      Ani, C.J., Cresswell, A., Haller-Bull, V., Gilmour, J. and Robson, B.J.
      https://doi.org/10.36334/modsim.2023.ani324
  • Croke, B.F.W.
    • Groundwater recharge estimation through unsaturated zone modelling
      Rannu, R.P., Croke, B.F.W., Merritt, W.S. and Mainuddin, M.
      https://doi.org/10.36334/modsim.2023.rannu
    • Assessing the contribution of hydrologic and climatic factors on vegetation condition changes in semi-arid wetlands: An analysis of the Narran Lakes
      Liu, M., Jakeman, A.J., Lerat, J., Hamilton, S.H., Jin, H., Croke, B.F.W. and Savage, C.
      https://doi.org/10.36334/modsim.2023.liu198
    • Virtual hydrological laboratories: Developing the next generation of conceptual models to support decision-making under change
      Thyer, M., Gupta, H., Westra, S., McInerney, D., Maier, H.R., Kavetski, D., Jakeman, A.J., Croke, B.F.W., Simmons, C.T., Shanafield, M., Partington, D. and Tague, C.
      https://doi.org/10.36334/modsim.2023.thyer
    • Runoff non-recovery of ACT water catchments
      Mana, S.C., Peterson, T.J., Lade, S.J., Croke, B.F.W. and Iwanaga, T.
      https://doi.org/10.36334/modsim.2023.mana
    • Calibration of the Floodplain Ecological Response Model
      Tan, D., Teng, J., Croke, B.F.W. and Iwanaga, T.
      https://doi.org/10.36334/modsim.2023.tan203
  • Crosswell, J.
    • Modelling the effect of river load reductions on water quality in the Crown of Thorns Starfish outbreak initiation zone of the Great Barrier Reef
      Robson, B.J., Crosswell, J. and Kroon, F.J.
      https://doi.org/10.36334/modsim.2023.robson
  • Cummins, S.J.
    • How to create and support families of deliverable software products from a common IP pool with high levels of software reuse in a workflow platform
      Thomas, D.G., Cummins, S.J. and Cleary, P.W.
      https://doi.org/10.36334/modsim.2023.thomas144
    • Building a simulation application for blasting: Case study of software component re-use and customisation in a workflow framework
      Cummins, S.J., Thomas, D.G., Sellers, E., Fathi Salmi, E. and Cleary, P.W.
      https://doi.org/10.36334/modsim.2023.cummins

D

  • Dabrowski, J.J.
    • An operational framework to automatically evaluate the quality of weather observations from third-party stations
      Shao, Q., Li, M., Dabrowski, J.J., Bakar, S., Rahman, A., Powell, A. and Henderson, B.
      https://doi.org/10.36334/modsim.2023.shao114
  • Dakos, V.
    • A review of quantitative resilience measurements: Gaps in the operationalisation of agency and diversity in resilience metrics
      Sanches, V.H., Crépin, A.S., Dakos, V., Donges, J.F., Guillaume, J.H.A., Haider, J.L., Iwanaga, T., Kwakkel, J.H., Lade, S.J., Quinlan, A.E., Quiñones, R., Rocha, J.C. and Vivas, J.
      https://doi.org/10.36334/modsim.2023.sanches
  • Daly, R.
    • Combining dynamic and conceptual models for managing water quality in reservoirs: Guidance from three case studies
      Newman, J.P., Makarewicz, A., Daly, R., Swaffer, B., van der Linden, L. and Harvy, C.
      https://doi.org/10.36334/modsim.2023.newman645
  • Dandy, G.C.
    • Supporting flood risk management by combining integrated modelling and participation
      van Delden, H., Vanhout, R., Radford, D.A., Riddell, G.A., Koks, E.E., Maier, H.R., Zecchin, A.C., Hitchcock, D., Ward, K. and Dandy, G.C.
      https://doi.org/10.36334/modsim.2023.vandelden676
  • Davis, M.
    • Development of an online weather and irrigation forecast decision support tool using an action learning process
      Sexton, J., Philippa, B., Melville, B., Schepen, A., Attard, S., Davis, M. and Everingham, Y.
      https://doi.org/10.36334/modsim.2023.sexton
  • Devane, M.
    • Net export of E. coli from the Toenepi wetland cannot be explained by growth of naturalized E. coli in the water column
      Muirhead, R.W., Stott, R., Sukias, J.P.S., Devane, M. and Cookson, A.L.
      https://doi.org/10.36334/modsim.2023.muirhead
  • Dharssi, I.
    • Implementation of a gridded river routing scheme for land surface models and evaluation of streamflow simulations across Australia
      Woldemeskel, F., Rüdiger, C., Khan, Z., Yamazaki, D., Zhang, H., Marthews, T., Hou, J., Dharssi, I. and Su, C.-H.
      https://doi.org/10.36334/modsim.2023.woldemeskel
    • Adapting JULES for improved hydrological predictions in Australia: Challenges, strategies and future plans
      Tian, S., Rüdiger, C., Renzullo, L.J., Dharssi, I., Marchionni, V., Woldemeskel, F., Frost, A. and Carrara, E.
      https://doi.org/10.36334/modsim.2023.tian575
  • Di Virgilio, G.
    • A new Python module to convert WRF regional climate projections into CORDEX-compliant datasets
      Tam, E., Di Virgilio, G., Vieira Rocha, C., Choudhury, D., Ji, F., Hannah, N. and Riley, M.
      https://doi.org/10.36334/modsim.2023.tam
    • Evaluation of precipitation extremes in ERA5-driven regional climate simulations
      Ji, F., Di Virgilio, G., Nishant, N., Tam, E., Evans, J.P., Kala, J., Andrys, J., Thomas, C. and Riley, M.
      https://doi.org/10.36334/modsim.2023.ji
  • Diakogiannis, F.
    • Application of denoising diffusion models in the augmentation of a regional dataset of inherent optical properties and applications for remote sensing
      Drayson, N., Diakogiannis, F., Cherukuru, N., Blondeau-Patissier, D. and Schroeder, T.
      https://doi.org/10.36334/modsim.2023.drayson
  • Dillon, S.
    • Prediction of wheat and barley phenology through integration of genomic prediction and a crop growth model
      Zheng, B., Brown, H., Zhao, Z.G., Wang, E., Huth, N.I., Dillon, S., Hyles, J., Rathjen, T., Bloomfield, M., Celestina, C., Hunt, J. and Trevaskis, B.
      https://doi.org/10.36334/modsim.2023.zheng289
  • Doble, R.
    • Assessing the potential impacts of well integrity failure on groundwater resources in Australia
      Doble, R., Mallants, D., Huddlestone-Holmes, C., Peeters, L.J.M., Kear, J., Turnadge, C., Wu, B., Noorduijn, S. and Arjomand, E.
      https://doi.org/10.36334/modsim.2023.doble
  • Donges, J.F.
    • A review of quantitative resilience measurements: Gaps in the operationalisation of agency and diversity in resilience metrics
      Sanches, V.H., Crépin, A.S., Dakos, V., Donges, J.F., Guillaume, J.H.A., Haider, J.L., Iwanaga, T., Kwakkel, J.H., Lade, S.J., Quinlan, A.E., Quiñones, R., Rocha, J.C. and Vivas, J.
      https://doi.org/10.36334/modsim.2023.sanches
  • Donohue, R.J.
    • Developing satellite-derived nitrogen stable isotope ratio grids to globally monitor terrestrial plant nitrogen availability for 1984–2022
      Yang, J., Zhang, H., Guo, Y., Donohue, R.J., McVicar, T.R., Ferrier, S., Müller, W., Lü, X., Fang, Y., Wang, X., Reich, P.B., Han, X. and Mokany, K.
      https://doi.org/10.36334/modsim.2023.yang582
  • Dowdy, A.
  • Downey, M.
    • Reporting on the evaluation of environmental outcomes of delivery of Commonwealth environmental water in the Murray–Darling Basin, Australia
      Cuddy, S.M., Tetreault-Campbell, S., Nolan, M., O'Sullivan, J., Downey, M. and Wignell, E.
      https://doi.org/10.36334/modsim.2023.cuddy688
  • Drayson, N.
    • Application of denoising diffusion models in the augmentation of a regional dataset of inherent optical properties and applications for remote sensing
      Drayson, N., Diakogiannis, F., Cherukuru, N., Blondeau-Patissier, D. and Schroeder, T.
      https://doi.org/10.36334/modsim.2023.drayson
    • Using in-situ hyperspectral reflectance data for cyanobacterial bloom monitoring and forecasting
      Joehnk, K.D., Biswas, T., Anstee, J., Ford, P., Drayson, N., Kerrisk, G. and Malthus, T.
      https://doi.org/10.36334/modsim.2023.joehnk
    • Mapping water quality in complex estuarine and coastal waters using deep learning models and high-resolution satellite imagery
      Unnithan, S.L.K., Cherukuru, N., Drayson, N. and Ingleton, T.
      https://doi.org/10.36334/modsim.2023.unnithan

Modelling to support planning for resilience in a changing world