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

Lachish, S.
- Modelling habitat suitability under hydrological change in aquatic habitats of northern Australia
  Stratford, D., Linke, S., Merrin, L., Lachish, S., Karim, F. and Kim, S.S.H.
  https://doi.org/10.36334/modsim.2023.stratford

Lade, S.J.
- 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
- 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

Laffan, S.W.
- The sensitivity of species distribution models to new data and the utility of putting uncertainty on the map
  Clemens, R., Schwenke, A., Bayraktarov, E. and Laffan, S.W.
  https://doi.org/10.36334/modsim.2023.clemens

Lahur, P.
- Surrogate model for CFD based on machine learning
  Rahman, A., Pereira, G.G., Kilby, P. and Lahur, P.
  https://doi.org/10.36334/modsim.2023.rahman37
- Using Lindenmayer systems for evolutionary design of static mixers
  Howard, D., Kilby, P., Lahur, P. and Pereira, G.G.
  https://doi.org/10.36334/modsim.2023.howard
- Rapid, accurate and convenient fluid dynamical modelling for real-world applications
  Pereira, G.G. and Lahur, P.
  https://doi.org/10.36334/modsim.2023.pereira

Lai, J.C.S.
- An efficient numerical method for studying noise generation in vortex-induced vibration of bluff bodies
  Rajamuni, M.M., Lai, J.C.S., Ravi, S., Young, J. and Tian, F.
  https://doi.org/10.36334/modsim.2023.rajamuni

Lang, S.
- Stochastic centring of BARRA rainfall space-time patterns in a hydrological model
  Scorah, M., Lang, S., Nathan, R. and Cressall, B.
  https://doi.org/10.36334/modsim.2023.scorah

Langsdorf, H.
- A light-hearted approach to a serious problem: Building “educated trust” in models
  O'Brien, K.R., Adams, M.P., Egger, F., Maxwell, P., Weber, T., Maier, H.R., Vilas, M.P., Shaw, M., Turner, R., Birkett, G.R., Hamilton, D.P., Langsdorf, H. and Baird, M.E.
  https://doi.org/10.36334/modsim.2023.obrien

Larkin, T.
- Machine learning–enabled missile system characterisation
  Larkin, T., Whitehouse, S., Mashford, B. and Yeung, T.
  https://doi.org/10.36334/modsim.2023.larkin

Lawes, R.
- Towards an AI agronomist: Developing fast and efficient methods for predicting crop growth using machine learning
  Powell, A., Kuhnert, P.M., Pagendam, D.E. and Lawes, R.
  https://doi.org/10.36334/modsim.2023.powell
- Building trust in continental-scale modelling in agriculture
  Richetti, J., Zheng, B., Navarro Garcia, J. and Lawes, R.
  https://doi.org/10.36334/modsim.2023.richetti

Lawrie, T.
- The TSX: Estimating long-term trends of Australia’s threatened and near-threatened species
  Lawrie, T., Heard, G. and Watmuff, J.
  https://doi.org/10.36334/modsim.2023.lawrie

Le Bodic, P.
- A simplified model for plant breeding
  Davis, K., Le Bodic, P., Ernst, A.T., Kapoor, R. and Garcia-Flores, R.
  https://doi.org/10.36334/modsim.2023.davis

Le, B.
- War, pandemic, and stock performance: A case of artificial intelligence–adopting firms
  Ho, L.T., Gan, C., Jin, S. and Le, B.
  https://doi.org/10.36334/modsim.2023.ho16

Le, T.D.
- 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

Le, T.H.L.
- An agent-based model for sustainable agricultural development in the Upper Mekong Delta of Vietnam
  Le, T.H.L., Welch, M.C., Moss, J., Vo, B. and Kristiansen, P.
  https://doi.org/10.36334/modsim.2023.le570

Le, T.P.
- Developing an agent-based simulation model to evaluate biosecurity inspection policies
  Baker, C.M., Le, T.P., Waring, T.K. and Robinson, A.P.
  https://doi.org/10.36334/modsim.2023.baker

Ledlow, G.
- 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

Lee, D.G.
- Evaluating the reliability of ChatGPT answers for safety management in chemical handling facilities
  Lee, D.G., Bae, S. and Baek, J.B.
  https://doi.org/10.36334/modsim.2023.lee384

Lee, G.
- Evaluating the impact of rainfall duration on the relationship between atmospheric moisture and extreme precipitation
  Kim, S., Lee, G. and Sharma, A.
  https://doi.org/10.36334/modsim.2023.kim530
- Discovering relationships among economic variables using machine learning techniques
  Guo, Y., Li, J., Lo, T., Zhu, Z., Lee, G. and Toscas, P.
  https://doi.org/10.36334/modsim.2023.guo139

Lee, H.
- A water-level based calibration of rainfall-runoff models using satellite altimetry data
  Jian, J., Ryu, D., Wang, Q.J. and Lee, H.
  https://doi.org/10.36334/modsim.2023.jian531

Lee, M.J.
- Estimate for risk reduction rate using fuzzy-AHP and Bayesian network
  Lee, M.J., Bae, S. and Baek, J.B.
  https://doi.org/10.36334/modsim.2023.lee303
- Optimization of dilution ventilation layout design of isolation building using CFD
  Kim, M.C., Lee, M.J. and Baek, J.B.
  https://doi.org/10.36334/modsim.2023.kim378

Lee, M.S.
- Analysis of South Korean basin hydrologic cycle using structural equation model
  Song, S.U., Lee, M.S., Ma, J.H. and Yoo, C.S.
  https://doi.org/10.36334/modsim.2023.song333
- Assessment of the impact of winter snowfall on the occurrence of forest fires in the east coast, Korea
  Ma, J.H., Lee, M.S., Song, S.U. and Yoo, C.S.
  https://doi.org/10.36334/modsim.2023.ma370

Leelawat, N.
- A business continuity assessment method using Earth observation data: Verification in industrial zones, Thailand
  Kodaka, A., Leelawat, N., Tang, J. and Kohtake, N.
  https://doi.org/10.36334/modsim.2023.kodaka
- Effective user interface and user experience design for disaster-related applications: A review
  Bhisitcharoentat, Y., Saengtabtim, K., Leelawat, N. and Tang, J.
  https://doi.org/10.36334/modsim.2023.bhisitcharoentat
- 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

Lei, X.
- Integration of the generalized complementary relationship into a lumped hydrological model for improving water balance partitioning
  Lei, X. and Cheng, L.
  https://doi.org/10.36334/modsim.2023.lei

Leigh, R.
- Barossa water security strategy: A demonstration of community leadership, strategic foresight, climate resilience and systems modelling
  Leigh, R., Kingsborough, A., Westra, S., Brettig, P. and Helfgott, A.
  https://doi.org/10.36334/modsim.2023.leigh

Leighton, B.
- Efficiently computing DGGS cell representations of spatial geometries
  Petridis, R., Yu, J., Leighton, B. and Cox, S.J.D.
  https://doi.org/10.36334/modsim.2023.petridis

Lemiale, V.
- Modelling self-evacuation archetypes to improve wildfire evacuation traffic simulations: A regional case study
  Singh, D., Bulumulla, C., Strahan, K., Gilbert, J., Gamage, P., Marquez, L. and Lemiale, V.
  https://doi.org/10.36334/modsim.2023.singh54

Lemon, D.
- Provena: A provenance system for large distributed modelling and simulation workflows
  Yu, J., Baker, P., Cox, S.J.D., Petridis, R., Freebairn, A.C., Mirza, F., Thomas, L., Tickell, S., Lemon, D. and Rezvani, M.
  https://doi.org/10.36334/modsim.2023.yu90

Lenzen, M.
- Tracing the environmental footprints of pesticide use by linking mechanistic environmental modelling to multi-region input-output analysis
  Tang, F.H.M., Malik, A., Li, M., Lenzen, M. and Maggi, F.
  https://doi.org/10.36334/modsim.2023.tang191

Leonard, M.
- Impact of infilling method on calibration of a stochastic weather generator
  Nguyen, D.C.H., Leonard, M., Westra, S. and Dutta, D.
  https://doi.org/10.36334/modsim.2023.nguyen478
- NARCliM1.5 projections over the southern Murray–Darling Basin, Australia
  Devanand, A., Leonard, M., Westra, S. and Nguyen, D.C.H.
  https://doi.org/10.36334/modsim.2023.devanand483
- Streamflow-based evaluation highlights discrepancies in stochastic rainfall model performance
  Nguyen, T., Bennett, B. and Leonard, M.
  https://doi.org/10.36334/modsim.2023.nguyen509
- Use of climatic partitions for stochastic rainfall modelling
  Nguyen, D.C.H., Leonard, M. and Westra, S.
  https://doi.org/10.36334/modsim.2023.nguyen480

Lerat, J.
- 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
- Beyond extremes: Characterisation of the 2022 Northern Rivers flood
  Lerat, J., Vaze, J., Ticehurst, C., Marvanek, S. and Wang, B.
  https://doi.org/10.36334/modsim.2023.lerat

Li Liu, D.
- Compound drought and extreme temperature impacts on Australian wheat yields under climate change
  Li, S., Wang, B., Li Liu, D., Huete, A. and Yu, Q.
  https://doi.org/10.36334/modsim.2023.li657

Li, C.
- Combining salinity and water management modelling for the Hawkesbury Nepean Valley
  Simpson, J., Podger, S., Li, C., Nicholls, J., Kumandur, K., Dunne, P., Beling, E. and Coen, F.
  https://doi.org/10.36334/modsim.2023.simpson120

Li, C.C.
- 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
- Impact of vegetation changes on evapotranspiration in northern China
  Li, C.C., Zhang, Y.Q., Chiew, F.H.S., Post, D.A., Yu, Q., Tian, J., Ma, N. and Zhang, X.Z.
  https://doi.org/10.36334/modsim.2023.li363

Li, G.
- Simulated efficiency of DMPP applications in reducing N2O emissions from Australian N-fertilized rainfed wheat cropping systems
  Xing, H., Li, G. and Schwenke, G.D.
  https://doi.org/10.36334/modsim.2023.xing579

Li, J.
- Discovering relationships among economic variables using machine learning techniques
  Guo, Y., Li, J., Lo, T., Zhu, Z., Lee, G. and Toscas, P.
  https://doi.org/10.36334/modsim.2023.guo139

Li, M.
- 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
- Tracing the environmental footprints of pesticide use by linking mechanistic environmental modelling to multi-region input-output analysis
  Tang, F.H.M., Malik, A., Li, M., Lenzen, M. and Maggi, F.
  https://doi.org/10.36334/modsim.2023.tang191

Li, R.
- Machine learning methods for flood prediction: A review of methods, their strengths and limitations
  Karim, F., Armin, M.A., Tychsen-Smith, L., Li, R. and Penton, D.J.
  https://doi.org/10.36334/modsim.2023.karim563
- Generalizability of deep-learning-based emulation of hydrodynamic flood models
  Li, R., Tychsen-Smith, L., Karim, F., Penton, D.J. and Armin, M.A.
  https://doi.org/10.36334/modsim.2023.li398
- Resource optimisation for geostationary communication satellites
  Gaudry, A., Li, R., Mak-Hau, V., Jacobs, M. and Kodithuwakkuge, J.
  https://doi.org/10.36334/modsim.2023.gaudry

Li, S.
- Compound drought and extreme temperature impacts on Australian wheat yields under climate change
  Li, S., Wang, B., Li Liu, D., Huete, A. and Yu, Q.
  https://doi.org/10.36334/modsim.2023.li657

Li, W.
- Comprehensive evaluation of the water-energy-food nexus in the Tarim River Basin, northwest China
  Chen, Y., Feng, M., Wang, Y. and Li, W.
  https://doi.org/10.36334/modsim.2023.chen313
- Recent changes in the water and ecological condition at the arid Tarim River Basin
  Li, W., Zhu, C. and Chen, Y.
  https://doi.org/10.36334/modsim.2023.li404

Li, Y.
- Changes in water resources and ecological environment in arid northwest China
  Zhu, C., Chen, Y. and Li, Y.
  https://doi.org/10.36334/modsim.2023.zhu406
- Variation in agricultural water demand and its attributions in the arid Tarim River Basin
  Fang, G. and Li, Y.
  https://doi.org/10.36334/modsim.2023.fang405
- Functionalities in eWater Source to address new challenges in hydrological modelling
  Nair, S., Moolman, J., Li, Y. and McCallum, S.
  https://doi.org/10.36334/modsim.2023.nair
- An optimization model for determining the degree of decentralization for nonpotable water reuse in Hong Kong
  Li, Y. and Lu, Z.
  https://doi.org/10.36334/modsim.2023.li561

Liedloff, A.
- Insights from modelling Australia’s tropical savannas
  Liedloff, A. and Cook, G.
  https://doi.org/10.36334/modsim.2023.liedloff

Lieper, I.
- 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

Lilburne, L.
- Simulation modelling to develop an index of inherent risk of nitrogen losses to water from New Zealand’s agricultural lands
  Cichota, R., Lilburne, L., Tait, A. and Snow, V.
  https://doi.org/10.36334/modsim.2023.cichota245
- Simulating crop rotations to improve estimates of nutrient losses using APSIM in HPC
  Cichota, R., Khaembah, E.N., Thomas, S., Lilburne, L., Vickers, S., Omondiagbe, P. and Tait, A.
  https://doi.org/10.36334/modsim.2023.cichota622

Linke, S.
- Modelling habitat suitability under hydrological change in aquatic habitats of northern Australia
  Stratford, D., Linke, S., Merrin, L., Lachish, S., Karim, F. and Kim, S.S.H.
  https://doi.org/10.36334/modsim.2023.stratford

Lintern, A.
- Contrasting sediment and nutrient export patterns across different hydrological regimes: A case study in the Great Barrier Reef catchments
  Liu, S., Guo, D., Bende-Michl, U., Lintern, A., Waters, D.K. and Wang, Q.
  https://doi.org/10.36334/modsim.2023.liu77
- Australia’s water quality trends over two decades
  Guo, D., Minaudo, C., Zhang, Q., Dupas, R., Liu, S., Zhang, K., Bende-Michl, U., Duvert, C. and Lintern, A.
  https://doi.org/10.36334/modsim.2023.guo615
- 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
- Hydroclimatic drivers of stream water quality over 27 years: The role of streamflow, temperature and seasonality
  Lintern, A., Sargent, R., Hagan, J., Wilson, P., Western, A.W., Plum, C. and Guo, D.
  https://doi.org/10.36334/modsim.2023.lintern

Liquet, B.
- Spatial autoregressive model for a Dirichlet distribution
  Nguyen, T., Moka, S., Mengersen, K. and Liquet, B.
  https://doi.org/10.36334/modsim.2023.nguyen242

Little, J.C.
- Earth systems to Anthropocene systems: An evolutionary, system-of-systems, convergence paradigm for interdependent societal challenges
  Little, J.C., Kaaronen, R.O., Hukkinen, J.I., Xiao, S., Sharpee, T., Farid, A.M., Nilchiani, R. and Barton, C.M.
  https://doi.org/10.36334/modsim.2023.little
- Development and evaluation of system dynamics education modules for socioenvironmental systems
  Costello, R. and Little, J.C.
  https://doi.org/10.36334/modsim.2023.costello

Littler, B.
- CattleAssess3D: 3D camera technology integrated with BeefSpecs drafting tool to assist ‘meeting market specifications’
  McPhee, M.J., Walmsley, B.J., Littler, B., Siddell, J.P., Toohey, E., Oddy, V.H., Falque, R., Virgona, A., Vidal-Calleja, T. and Alempijevic, A.
  https://doi.org/10.36334/modsim.2023.mcphee

Liu, B.
- Impacts of climate extremes on vegetation phenology and productivity in a transect along the Hu Line of China
  Wang, H., Guan, H., Liu, B. and Chen, X.
  https://doi.org/10.36334/modsim.2023.wang19

Liu, D.L.
- Water and nitrogen use and productivity of dryland mixed farming system under climate change
  Wang, Z.K., Liu, D.L., Wang, B. and Cowie, A.
  https://doi.org/10.36334/modsim.2023.wang134
- Estimating wheat grain weight using UAV-multispectral imagery and machine learning
  Yao, S., Wang, B., Liu, D.L., Jin, X., Xia, H. and Yu, Q.
  https://doi.org/10.36334/modsim.2023.yao674
- Soil with high plant available water capacity can mitigate the agricultural drought effects on wheat biomass dynamic change
  Xiang, K., Wang, B., Liu, D.L., Huete, A. and Yu, Q.
  https://doi.org/10.36334/modsim.2023.xiang

Liu, L.
- Comparing the observed and predicted actual evapotranspiration in lumped conceptual hydrological models
  Liu, L., Vervoort, R.W., Johnson, F.M. and Marshall, L.A.
  https://doi.org/10.36334/modsim.2023.liu311

Liu, M.
- 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

Liu, N.
- The effects of forest disturbance and recovery on water in Mediterranean eucalypt forests of southwestern Australia
  Liu, N.
  https://doi.org/10.36334/modsim.2023.liu491
- "Good enough" principles for reproducibility: Developing pragmatic guidelines for early career scholars
  Iwanaga, T., Salazar, J.Z., Fischer, S.M., Jovanović, R., Liu, N., Zhu, Z. and Zhu, L.-J.
  https://doi.org/10.36334/modsim.2023.iwanaga485

Liu, P.
- A parametric Budyko method for representing actual reservoir operations
  Liu, W. and Liu, P.
  https://doi.org/10.36334/modsim.2023.liu360
- Detecting multidecadal variation of short-term drought risk by combining frequency analysis and Fourier transformation methods: A case study in the Yangtze River Basin
  Zou, K., Cheng, L., Zhang, Q., Qin, S., Liu, P. and Wu, M.
  https://doi.org/10.36334/modsim.2023.zou453
- Underestimated climate change impacts on hydro-wind-photovoltaic complementary power systems
  Cheng, Q. and Liu, P.
  https://doi.org/10.36334/modsim.2023.cheng359

Liu, S.
- Australia’s water quality trends over two decades
  Guo, D., Minaudo, C., Zhang, Q., Dupas, R., Liu, S., Zhang, K., Bende-Michl, U., Duvert, C. and Lintern, A.
  https://doi.org/10.36334/modsim.2023.guo615
- Contrasting sediment and nutrient export patterns across different hydrological regimes: A case study in the Great Barrier Reef catchments
  Liu, S., Guo, D., Bende-Michl, U., Lintern, A., Waters, D.K. and Wang, Q.
  https://doi.org/10.36334/modsim.2023.liu77
- Using remotely sensed data to understand global lake colour variability
  Liu, S., Glamore, W., Liu, Y. and Johnson, F.M.
  https://doi.org/10.36334/modsim.2023.liu327
- Characterising thermal anomalies during Amazon droughts using multiple satellite observations
  Liu, S., McVicar, T.R. and Liu, Y.
  https://doi.org/10.36334/modsim.2023.liu522

Liu, W.
- Spatial modelling of understorey evapotranspiration based on the maximum entropy production method
  Liu, W., Guan, H., Bruce, D., Batelaan, O., Keane, R., Keegan-Treloar, R., Gutiérrez-Jurado, K.Y., Thompson, J. and Wang, J.
  https://doi.org/10.36334/modsim.2023.liu287
- Predicting surface-specific humidity from radiative temperature and ambient weather for evapotranspiration modelling
  Gou, J., Liu, W., Guan, H., Batelaan, O., Bruce, D., Gutierrez, K., Wang, H., Gutierrez, H., Burk, L., Thompson, J. and Woods, J.
  https://doi.org/10.36334/modsim.2023.gou
- A parametric Budyko method for representing actual reservoir operations
  Liu, W. and Liu, P.
  https://doi.org/10.36334/modsim.2023.liu360

Liu, Y.
- Characterising thermal anomalies during Amazon droughts using multiple satellite observations
  Liu, S., McVicar, T.R. and Liu, Y.
  https://doi.org/10.36334/modsim.2023.liu522
- Using remotely sensed data to understand global lake colour variability
  Liu, S., Glamore, W., Liu, Y. and Johnson, F.M.
  https://doi.org/10.36334/modsim.2023.liu327
- Greening of vegetation and climate change promote an increase in evapotranspiration and transpiration fraction in the Yellow River Basin, China
  Liu, Y.
  https://doi.org/10.36334/modsim.2023.liu519

Liu, Z.
- A large difference in rain use efficiency among Australian terrestrial ecosystems
  Liu, Z., Guan, H., Batelaan, O. and Grzegorz, S.
  https://doi.org/10.36334/modsim.2023.liu258

Lo, M.
- Limited impacts of a permanent inland lake in central Australia on local-to-regional precipitation
  Yang, Z., Ryu, D., Lo, M., Narsey, S., Peel, M.C. and McColl, K.
  https://doi.org/10.36334/modsim.2023.yang280

Lo, T.
- Discovering relationships among economic variables using machine learning techniques
  Guo, Y., Li, J., Lo, T., Zhu, Z., Lee, G. and Toscas, P.
  https://doi.org/10.36334/modsim.2023.guo139

Loades, K.
- Cross-scale analysis of social-ecological systems: Policy options appraisal for delivering NetZero and other environmental objectives in Scotland
  Matthews, K.B., Blackstock, K.L., Wardell-Johnson, D.H., Miller, D.G., Tavana, M., Thomson, S., Moxey, A., Nielsen, R., Baggaley, N., Loades, K., Paterson, E., Pakeman, R., Hawes, C., Stockan, J., Stutter, M., Addy, S. and Wilkinson, M.
  https://doi.org/10.36334/modsim.2023.matthews

Lodge, J.M.
- Mathematical modelling demonstrates how students can get stuck in unproductive learning regimes
  Egger, F., Lodge, J.M., Adams, M.P., Birkett, G.R., Monsalve-Bravo, G.M., Howes, T. and O'Brien, K.R.
  https://doi.org/10.36334/modsim.2023.egger512

Lohani, B.
- Relative performance evaluation of LiDAR and Cartosat DEMs for surface rainwater harvesting site identification
  Kommula, S.P., Lohani, B., Ryu, D. and Winter, S.
  https://doi.org/10.36334/modsim.2023.kommula

Lohr, H.
- Continuous3D, an end-to-end solution for robotic additive manufacturing
  Lohr, H., King, P., Vargas, A., Chu, C., Roberts, J. and Teixeira, M.
  https://doi.org/10.36334/modsim.2023.lohr

London, A.
- Practical guidance for developing causal network topology
  Peeters, L.J.M., Holland, K. and London, A.
  https://doi.org/10.36334/modsim.2023.peeters
- Conceptualising causal networks for environmental impact assessment
  Holland, K., Peeters, L.J.M. and London, A.
  https://doi.org/10.36334/modsim.2023.holland
- Going beyond Word: Convincing scientists to embrace content management systems for writing science content
  London, A., Tetreault-Campbell, S., Holland, K. and Peeters, L.J.M.
  https://doi.org/10.36334/modsim.2023.london

Long, W.
- Modeling of radiative free cooling for data centers
  Long, W. and Aili, A.
  https://doi.org/10.36334/modsim.2023.long52

Longmuir, D.N.R.
- A metapopulation model of Little Red Flying Fox population dynamics across Queensland
  Longmuir, D.N.R., Hoskins, A.J. and Hickson, R.I.
  https://doi.org/10.36334/modsim.2023.longmuir

Loonat, N.
- River system modelling to inform Murrumbidgee and NSW Murray regional water strategies
  Dutta, D., Podger, G.M., Trim, A., Cu, T.P., Loonat, N., Matsinos, A., Taylor, N. and Driver, P.D.
  https://doi.org/10.36334/modsim.2023.dutta
- Role of modelling and monitoring hub in fostering interagency collaboration
  Loonat, N., Baker, D., Joyner, A. and Couriel, E.
  https://doi.org/10.36334/modsim.2023.loonat

Lourey, H.
- Optimising the unpredictability of a ballistic missile
  Comino, E., Ogilvie, J., King, M., Lourey, H. and Wharington, J.
  https://doi.org/10.36334/modsim.2023.comino

Low-Choy, S.
- Generalising the raindrop plot for prediction and variable selection: An educational case study
  Vasco, D., Low-Choy, S. and Singh, P.
  https://doi.org/10.36334/modsim.2023.vasco
- Bayesian decision-theoretic analysis of thresholds in Gompertz-mixture models, for robust detection of corona-like viruses in wildlife
  Low-Choy, S., McKinley, T.J., Pulscher, L. and Peel, A.
  https://doi.org/10.36334/modsim.2023.lowchoy656
- Multiverse experiments for enhancing reproducibility and resilience of statistical modelling via case studies in family wellbeing and biodiversity conservation
  Low-Choy, S., Modecki, K., Vasco, D., Alkhairy, I. and Hallgren, W.
  https://doi.org/10.36334/modsim.2023.lowchoy654

Lu, G.
- Study on sharing and reusing geographic simulation models in web environment
  Xu, K., Chen, M., Yue, S., Wen, Y., Zhang, F., Wang, J. and Lu, G.
  https://doi.org/10.36334/modsim.2023.xu225

Lü, X.
- 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

Lu, Z.
- An optimization model for determining the degree of decentralization for nonpotable water reuse in Hong Kong
  Li, Y. and Lu, Z.
  https://doi.org/10.36334/modsim.2023.li561

Lucchesi, L.R.
- VizumApp: A tool for visualising predictions and uncertainties from spatial models
  Kuhnert, P.M., Nelson, S., Lucchesi, L.R., Chin, B., Pagendam, D.E. and Janardhanan, S.
  https://doi.org/10.36334/modsim.2023.kuhnert

Luxton, S.
- Can we use state and transition models to add dynamism to fire risk and behaviour models?
  Furlaud, J.M., Szetey, K., Luxton, S., Newnham, G., Williams, K.J., Prober, S. and Richards, A.
  https://doi.org/10.36334/modsim.2023.furlaud

Lyell, C.S.
- A seven-day ahead bushfire fuel moisture forecasting system integrating an automated fuel sensor network, weather forecasts and a machine learning model
  Keeble, T.P., Lyell, C.S. and Sheridan, G.
  https://doi.org/10.36334/modsim.2023.keeble

Lynch, S.K.
- 'Stat on pixels': An automated counting method for selective fluorescent-stained microplastics using Nile Red dye
  Athukorala, R., Lynch, S.K., Johnson, C., Suzzi, A.L., Rao, S. and Foulsham, E.L.
  https://doi.org/10.36334/modsim.2023.athukorala548

Lyu, J.
- Medical decision making: Microsimulation versus cohort modelling for assessing type 2 diabetes treatments
  Lyu, J. and Kim, H.
  https://doi.org/10.36334/modsim.2023.lyu

Ma, J.H.
- Analysis of South Korean basin hydrologic cycle using structural equation model
  Song, S.U., Lee, M.S., Ma, J.H. and Yoo, C.S.
  https://doi.org/10.36334/modsim.2023.song333
- Assessment of the impact of winter snowfall on the occurrence of forest fires in the east coast, Korea
  Ma, J.H., Lee, M.S., Song, S.U. and Yoo, C.S.
  https://doi.org/10.36334/modsim.2023.ma370

Ma, N.
- Impact of vegetation changes on evapotranspiration in northern China
  Li, C.C., Zhang, Y.Q., Chiew, F.H.S., Post, D.A., Yu, Q., Tian, J., Ma, N. and Zhang, X.Z.
  https://doi.org/10.36334/modsim.2023.li363
- Recovery of fire-impacted ecosystems: Detection using a state-of-the-art diagnostic evapotranspiration model
  Xu, Z.W., Zhang, Y.Q. and Ma, N.
  https://doi.org/10.36334/modsim.2023.xu342
- Impacts of drought on crop yield in the semiarid region
  Yang, X.N., Zhang, Y.Q., Tian, J., Zhang, X.Z., Ma, N. and Zhao, Z.G.
  https://doi.org/10.36334/modsim.2023.yang410
- Detecting ecosystem resilience to drought across 119 flux tower stations
  Shao, X.M., Zhang, Y.Q., Tian, J., Ma, N., Zhang, X.Z. and Xu, Z.W.
  https://doi.org/10.36334/modsim.2023.shao343
- 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
- Is global hydrological cycle accelerating at the centennial scale? A perspective from land evapotranspiration
  Ma, N., Zhang, Y.Q. and Szilagyi, J.
  https://doi.org/10.36334/modsim.2023.ma219

Ma, W.
- Statistical analysis of Continuous Haines Index and Fuel Moisture Index for pyrocumulonimbus and non-pyrocumulonimbus bushfires in southeast Australia
  Wilson, C.S., Ma, W., Sharples, J.J. and Evans, J.P.
  https://doi.org/10.36334/modsim.2023.wilson

Ma, Y.
- Regionalization of land surface heat fluxes and evapotranspiration by using satellite data and atmospheric boundary layer observations over the Third Pole
  Ma, Y.
  https://doi.org/10.36334/modsim.2023.ma505
- How land surface heterogeneity impacts on energy partitioning and atmospheric boundary development
  Han, C. and Ma, Y.
  https://doi.org/10.36334/modsim.2023.han529

Ma, Z.
- Promoting forest landscape dynamic prediction: An online collaboration framework
  Ma, Z. and Chen, M.
  https://doi.org/10.36334/modsim.2023.ma197

Macdonald, B.
- Cross-scale modelling of cropping systems: from gene/genome to landscape in era of big data
  Wang, E., Brown, H., Trevaskis, B., Zheng, B., Rebetzke, G., Zhao, Z.G., Huth, N.I., He, D., Hyles, J., Glover, M., Malone, B. and Macdonald, B.
  https://doi.org/10.36334/modsim.2023.wang299

Mackay, A.D.
- Soil health modelling with APSIM
  Dodd, M.B., Schon, N. and Mackay, A.D.
  https://doi.org/10.36334/modsim.2023.dodd

MacKinlay, D.
- Stochastic emulators for prediction of noisy physical systems with METHO
  MacKinlay, D., Tong, R., Tsuchida, R., Pagendam, D.E., Janardhanan, S. and Kuhnert, P.M.
  https://doi.org/10.36334/modsim.2023.mackinlay
- Calibration and uncertainty analysis of groundwater models assisted by machine learning surrogates
  Janardhanan, S., Pagendam, D.E., MacKinlay, D., Pickett, T. and Kuhnert, P.M.
  https://doi.org/10.36334/modsim.2023.janardhanan

Madhushankha, J.M.L.
- A first step towards the derivation of non-stationary design rainfalls for Australia
  Madhushankha, J.M.L., Wasko, C., Nathan, R. and Johnson, F.M.
  https://doi.org/10.36334/modsim.2023.madhushankha

Maggi, F.
- Tracing the environmental footprints of pesticide use by linking mechanistic environmental modelling to multi-region input-output analysis
  Tang, F.H.M., Malik, A., Li, M., Lenzen, M. and Maggi, F.
  https://doi.org/10.36334/modsim.2023.tang191

Maguire, S.
- Towards scalable and reproducible hydrological modelling with HydroMT: A proof of concept for Australia
  Hegnauer, M., Maguire, S., Eilander, D. and Boisgontier, H.
  https://doi.org/10.36334/modsim.2023.hegnauer

Maier, H.R.
- Improved understanding of wildfire risk through simulating dynamic exposure profiles
  van Delden, H., Vanhout, R., Jeanneau, A., Maier, H.R. and Zecchin, A.C.
  https://doi.org/10.36334/modsim.2023.vandelden678
- 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
- Building capacity to achieve sustainable outcomes for wicked problems
  Maier, H.R. and Culley, S.
  https://doi.org/10.36334/modsim.2023.maier61
- Integrated natural hazard risk management: A two-week intensive course
  Maier, H.R., Jeanneau, A., Radford, D.A. and He, L.
  https://doi.org/10.36334/modsim.2023.maier62
- Developing complex environmental modelling skills through project-centric teaching
  Maier, H.R.
  https://doi.org/10.36334/modsim.2023.maier60
- A light-hearted approach to a serious problem: Building “educated trust” in models
  O'Brien, K.R., Adams, M.P., Egger, F., Maxwell, P., Weber, T., Maier, H.R., Vilas, M.P., Shaw, M., Turner, R., Birkett, G.R., Hamilton, D.P., Langsdorf, H. and Baird, M.E.
  https://doi.org/10.36334/modsim.2023.obrien
- 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
- Adaptive operation policies for reservoir management in a changing world
  Huang, J., Wu, W., Wang, Q.J., Maier, H.R. and Hughes, J.D.
  https://doi.org/10.36334/modsim.2023.huang

Mainuddin, M.
- Pathway to impact: Sustainable Development Investment Portfolio
  Wahid, S., Cuddy, S.M., Ahmad, M.D., Mainuddin, M. and Almeida, A.C.
  https://doi.org/10.36334/modsim.2023.wahid
- 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
- Sustaining groundwater irrigation for food security in the northwest region of Bangladesh
  Mainuddin, M.
  https://doi.org/10.36334/modsim.2023.mainuddin

Majhi, R.C.
- Exploring user intention for dynamic wireless charging facilities: Some insights from a survey in New Zealand
  Majhi, R.C., Ranjitkar, P. and Sheng, M.S.
  https://doi.org/10.36334/modsim.2023.majhi

Makarewicz, A.
- 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

Mak-Hau, V.
- Resource optimisation for geostationary communication satellites
  Gaudry, A., Li, R., Mak-Hau, V., Jacobs, M. and Kodithuwakkuge, J.
  https://doi.org/10.36334/modsim.2023.gaudry

Malik, A.
- Tracing the environmental footprints of pesticide use by linking mechanistic environmental modelling to multi-region input-output analysis
  Tang, F.H.M., Malik, A., Li, M., Lenzen, M. and Maggi, F.
  https://doi.org/10.36334/modsim.2023.tang191

Mallants, D.
- 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

Malone, B.
- Trends and drivers of carbon stocks across rangelands over the decade 2010–2020
  Pasut, C., Karunaratne, S., Malone, B., Shepherd, N. and Zwartz, D.
  https://doi.org/10.36334/modsim.2023.pasut
- Cross-scale modelling of cropping systems: from gene/genome to landscape in era of big data
  Wang, E., Brown, H., Trevaskis, B., Zheng, B., Rebetzke, G., Zhao, Z.G., Huth, N.I., He, D., Hyles, J., Glover, M., Malone, B. and Macdonald, B.
  https://doi.org/10.36334/modsim.2023.wang299

Malthus, T.
- 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

Mana, S.C.
- 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

Manning, C.
- Quantifying changes in climate resilience of our electricity networks
  Wilkinson, S., Manning, C., Dunn, S. and Fowler, H.
  https://doi.org/10.36334/modsim.2023.wilkinson

Mao, Y.N.
- Study on the impact of ubiquitous sensing of rainfall data on hydrological simulation
  Wang, J., Khu, S.T. and Mao, Y.N.
  https://doi.org/10.36334/modsim.2023.wang45

Marchionni, V.
- 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

Margvelashvili, N.
- Simulated deposition of aeolian dust on the Australian continental shelf: Preliminary results
  Margvelashvili, N., Skerratt, J.H., Mongin, M., Baird, M.E. and Wild-Allen, K.
  https://doi.org/10.36334/modsim.2023.margvelashvili

Marial, O.
- Improving access and efficiency in care delivery for patients with spinal cord injury in NSW Australia: A discrete-event dynamic simulation modelling approach
  Assareh, H., Pavlov, V., Adarkar, K., Johnson, J., Fortunato, R., Marial, O. and Middleton, J.
  https://doi.org/10.36334/modsim.2023.assareh

Marquez, L.
- Behavioural survey for cognitive agent modelling in earthquake evacuation
  Rollan, T.A., Marquez, L. and Chua, C.
  https://doi.org/10.36334/modsim.2023.rollan
- Modelling self-evacuation archetypes to improve wildfire evacuation traffic simulations: A regional case study
  Singh, D., Bulumulla, C., Strahan, K., Gilbert, J., Gamage, P., Marquez, L. and Lemiale, V.
  https://doi.org/10.36334/modsim.2023.singh54

Marshall, J.
- Mapping the risk of disease transmission between wild bovids and domestic livestock in Thailand
  Horpiencharoen, W., Marshall, J., Muylaert, R.L., John, R.S. and Hayman, D.T.S.
  https://doi.org/10.36334/modsim.2023.horpiencharoen

Marshall, L.A.
- Resampling techniques for rare events prediction using data-driven and hydrological models
  Zeinolabedini Rezaabad, M., Marshall, L.A. and Johnson, F.M.
  https://doi.org/10.36334/modsim.2023.zeinolabedini
- Microwave data and climate information–based streamflow prediction using the surrogate river discharge model in the Murray–Darling Basin
  Yoon, H.N., Marshall, L.A. and Sharma, A.
  https://doi.org/10.36334/modsim.2023.yoon
- Comparing the observed and predicted actual evapotranspiration in lumped conceptual hydrological models
  Liu, L., Vervoort, R.W., Johnson, F.M. and Marshall, L.A.
  https://doi.org/10.36334/modsim.2023.liu311
- Modelling the impacts of future evapotranspiration changes on streamflow
  Jian, J., Johnson, F.M. and Marshall, L.A.
  https://doi.org/10.36334/modsim.2023.jian467
- Modelling future gross primary productivity in Australia
  Zou, H., Marshall, L.A. and Sharma, A.
  https://doi.org/10.36334/modsim.2023.zou336

Marshall, S.K.
- Using expert participation to evaluate the accuracy and variability of hand-drawn water table mapping
  Marshall, S.K., Batelaan, O. and Peeters, L.J.M.
  https://doi.org/10.36334/modsim.2023.marshall

Marthews, T.
- 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

Martin, J.
- Data-driven risk mitigation: Water quality forecasting during extreme events
  Rumman, R., Martin, J., van der Sterren, M., Chen, C., Abdollahian, M.A. and Hughes, D.
  https://doi.org/10.36334/modsim.2023.rumman
- System design for integrated water modelling
  Chen, C., van der Sterren, M. and Martin, J.
  https://doi.org/10.36334/modsim.2023.chen321

Martin, T.
- Estimating recreational catch
  Mendiolar, M., Filar, J.A., O'Neill, M.F., Martin, T., Teixeira, D., Webley, J. and Holden, M.
  https://doi.org/10.36334/modsim.2023.mendiolar

Marvanek, S.
- Inundation frequency in the Murray–Darling Basin: Past, present and future
  Teng, J., Chiew, F.H.S., Yang, A., Zheng, H., Penton, D.J., Ticehurst, C., Marvanek, S., Vaze, J. and Khanam, F.
  https://doi.org/10.36334/modsim.2023.teng320
- A large-scale flexible mesh 2D hydrodynamic model for the Cooper Creek floodplain
  Mateo, C.M., Vaze, J., Wang, B., Kim, S.S.H., Marvanek, S., Ticehurst, C., Crosbie, R.S. and Holland, K.
  https://doi.org/10.36334/modsim.2023.mateo
- Two-monthly maximum water depth for the Murray–Darling Basin: Usage guidance
  Penton, D.J., Teng, J., Ticehurst, C., Marvanek, S., Freebairn, A.C., Vaze, J., Khanam, F. and Sengupta, A.
  https://doi.org/10.36334/modsim.2023.penton
- Beyond extremes: Characterisation of the 2022 Northern Rivers flood
  Lerat, J., Vaze, J., Ticehurst, C., Marvanek, S. and Wang, B.
  https://doi.org/10.36334/modsim.2023.lerat
- New approaches in modelling Basin-scale connectivity and ecological relevance
  Sengupta, A., Stratford, D. and Marvanek, S.
  https://doi.org/10.36334/modsim.2023.sengupta

Mashford, B.
- Machine learning–enabled missile system characterisation
  Larkin, T., Whitehouse, S., Mashford, B. and Yeung, T.
  https://doi.org/10.36334/modsim.2023.larkin

Maskell, P.
- Building a one-vs-all classifier for spatial prediction of detected pathogens
  Maskell, P., Ryan, M., Karawita, A., Hickson, R.I. and Golchin, M.
  https://doi.org/10.36334/modsim.2023.maskell

Mata, G.
- A method to improve the efficiency of calibrating biophysical models for pastures
  Thomas, D.T., Chen, C., Ota, N., Mata, G., Murphy, S.R., Giblin, S. and Beale, P.J.
  https://doi.org/10.36334/modsim.2023.thomas105

Matala, A.
- Building a modern, all-purpose hydrological forecasting system
  Matala, A., Hunter, J., Robinson, K. and Bennett, J.C.
  https://doi.org/10.36334/modsim.2023.matala

Mateo, C.M.
- Flow regime changes in the Murray–Darling Basin over the past 50 years and implications for river systems models
  Crosbie, R.S., Wang, B., Kim, S.S.H., Mateo, C.M. and Vaze, J.
  https://doi.org/10.36334/modsim.2023.crosbie182
- A large-scale flexible mesh 2D hydrodynamic model for the Cooper Creek floodplain
  Mateo, C.M., Vaze, J., Wang, B., Kim, S.S.H., Marvanek, S., Ticehurst, C., Crosbie, R.S. and Holland, K.
  https://doi.org/10.36334/modsim.2023.mateo

Mathur, A.
- A continuous optimization algorithm for column subset selection
  Mathur, A., Moka, S. and Botev, Z.
  https://doi.org/10.36334/modsim.2023.mathur

Matsinos, A.
- River system modelling to inform Murrumbidgee and NSW Murray regional water strategies
  Dutta, D., Podger, G.M., Trim, A., Cu, T.P., Loonat, N., Matsinos, A., Taylor, N. and Driver, P.D.
  https://doi.org/10.36334/modsim.2023.dutta

Matthews, K.
- Using multi-replicate source modelling to create a probabilistic storage forecasting tool
  Austin, K., Neal, B., Guthrie, E., Scorah, M., Matthews, K. and Jordan, P.
  https://doi.org/10.36334/modsim.2023.austin

Matthews, K.B.
- Cross-scale analysis of social-ecological systems: Policy options appraisal for delivering NetZero and other environmental objectives in Scotland
  Matthews, K.B., Blackstock, K.L., Wardell-Johnson, D.H., Miller, D.G., Tavana, M., Thomson, S., Moxey, A., Nielsen, R., Baggaley, N., Loades, K., Paterson, E., Pakeman, R., Hawes, C., Stockan, J., Stutter, M., Addy, S. and Wilkinson, M.
  https://doi.org/10.36334/modsim.2023.matthews

Mátyás, L.
- Estimation with pairwise observations
  Chan, F., Mátyás, L. and Reizinger, K.
  https://doi.org/10.36334/modsim.2023.chan555

Maxwell, P.
- A light-hearted approach to a serious problem: Building “educated trust” in models
  O'Brien, K.R., Adams, M.P., Egger, F., Maxwell, P., Weber, T., Maier, H.R., Vilas, M.P., Shaw, M., Turner, R., Birkett, G.R., Hamilton, D.P., Langsdorf, H. and Baird, M.E.
  https://doi.org/10.36334/modsim.2023.obrien

May, D.
- Modelling stormwater harvesting for environmental flows
  Denson, E., Godoy, W., Gourley, J., May, D., van Ryn, P. and Yan, W.
  https://doi.org/10.36334/modsim.2023.denson

McCallum, A.
- Simulating the impacts of reduced streamflow on localised groundwater recharge in NSW
  Crosbie, R.S., Charles, S., Fu, G., Hodgson, G., Dutta, D. and McCallum, A.
  https://doi.org/10.36334/modsim.2023.crosbie259

McCallum, S.
- A guide to future climate projections for water resource management in Western Australia
  Schopf, J., Kitsios, A., McCallum, S., Turner, M., Bende-Michl, U. and Hall, J.
  https://doi.org/10.36334/modsim.2023.schopf
- Functionalities in eWater Source to address new challenges in hydrological modelling
  Nair, S., Moolman, J., Li, Y. and McCallum, S.
  https://doi.org/10.36334/modsim.2023.nair

McCarthy, D.
- 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

McCarthy, M.
- A partially observed approach to invasive species management: To monitor or control?
  Waring, T.K., Somers, V., McCarthy, M. and Baker, C.M.
  https://doi.org/10.36334/modsim.2023.waring

McCarthy, N.F.
- Bottlenecks, feedbacks and thresholds in wildfire suppression
  McCarthy, N.F., Duff, T., Butler, K. and Deutsch, S.
  https://doi.org/10.36334/modsim.2023.mccarthy

McCloskey, G.L.
- Fire, fine sediment, and fractional ground cover: Representation of fire in the Cape York – Great Barrier Reef water quality model
  Pollett, A. and McCloskey, G.L.
  https://doi.org/10.36334/modsim.2023.pollett

McColl, K.
- Limited impacts of a permanent inland lake in central Australia on local-to-regional precipitation
  Yang, Z., Ryu, D., Lo, M., Narsey, S., Peel, M.C. and McColl, K.
  https://doi.org/10.36334/modsim.2023.yang280

McComb, J.
- Long-range impact-based forecasts for agricultural drought early warning in Australia
  Schepen, A., Hughes, N., Gaydon, D., Sharman, C., McComb, J., Mitchell, P. and Carter, J.
  https://doi.org/10.36334/modsim.2023.schepen

McCullough, D.P.
- Changing climate and the uncertainties in allocating water for consumptive and environmental needs in highly developed catchments
  Savadamuthu, K., McCullough, D.P. and Green, D.
  https://doi.org/10.36334/modsim.2023.savadamuthu
- Hydrodynamic and hydrological modelling to assess benefits, risks, and trade-offs from engineered flooding with a limited water resource
  Montazeri, M., McCullough, D.P. and Gibbs, M.S.
  https://doi.org/10.36334/modsim.2023.montazeri

McDowell, R.W.
- Some challenges with farm-to-fork modelling
  Kaye-Blake, W.H. and McDowell, R.W.
  https://doi.org/10.36334/modsim.2023.kayeblake

McGree, J.M.
- Managing surgical waiting lists through dynamic priority scoring
  Powers, J., McGree, J.M., Grieve, D., Aseervatham, R., Ryan, S. and Corry, P.
  https://doi.org/10.36334/modsim.2023.powers

McInerney, D.
- 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

McIntyre, N.
- Bias-correcting regional climate models for rainfall erosivity projections: How much does it matter?
  Bulovic, N., McIntyre, N., Trancoso, R., Bolz, P. and Shaygan, M.
  https://doi.org/10.36334/modsim.2023.bulovic618
- Evaluating downscaled CMIP5 and CMIP6 for rainfall erosivity projections
  Bulovic, N., McIntyre, N., Trancoso, R., Bolz, P. and Shaygan, M.
  https://doi.org/10.36334/modsim.2023.bulovic428

McKinley, T.J.
- Bayesian decision-theoretic analysis of thresholds in Gompertz-mixture models, for robust detection of corona-like viruses in wildlife
  Low-Choy, S., McKinley, T.J., Pulscher, L. and Peel, A.
  https://doi.org/10.36334/modsim.2023.lowchoy656

McPhee, M.J.
- CattleAssess3D: 3D camera technology integrated with BeefSpecs drafting tool to assist ‘meeting market specifications’
  McPhee, M.J., Walmsley, B.J., Littler, B., Siddell, J.P., Toohey, E., Oddy, V.H., Falque, R., Virgona, A., Vidal-Calleja, T. and Alempijevic, A.
  https://doi.org/10.36334/modsim.2023.mcphee

McVicar, T.R.
- Characterising thermal anomalies during Amazon droughts using multiple satellite observations
  Liu, S., McVicar, T.R. and Liu, Y.
  https://doi.org/10.36334/modsim.2023.liu522
- 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

Meason, D.
- Integrated modelling of forest growth and hydrologic processes for forest management
  Yang, J., White, D., Palma, J.H.N., Meason, D., Balocchi, F. and Rajanayaka, C.
  https://doi.org/10.36334/modsim.2023.yang393

Meechang, K.
- 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

Meler, E.
- Stock and flow modelling of a veterinary teaching hospital: How to better embed clinical teaching into patient flow
  Meler, E., Schull, D., Kelly, S. and Richards, R.
  https://doi.org/10.36334/modsim.2023.meler

Melsen, L.A.
- Building trust: How modellers navigate dozens of decisions
  Remmers, J.O.E. and Melsen, L.A.
  https://doi.org/10.36334/modsim.2023.remmers

Melton, D.
- System dynamics and resilience in the pro-sport athletic department: Towards a capability-based theory
  Melton, D.
  https://doi.org/10.36334/modsim.2023.melton

Melville, B.
- 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

Menberg, K.
- Modelling the impact of climate change on global groundwater temperatures
  Benz, S.A., Irvine, D.J., Rau, G.C., Bayer, P., Menberg, K., Blum, P., Jamieson, R.C., Griebler, C. and Kurylyk, B.L.
  https://doi.org/10.36334/modsim.2023.benz

Mendiolar, M.
- Estimating recreational catch
  Mendiolar, M., Filar, J.A., O'Neill, M.F., Martin, T., Teixeira, D., Webley, J. and Holden, M.
  https://doi.org/10.36334/modsim.2023.mendiolar

Menesch, J.
- Automated adaptive multilevel splitting
  Menesch, J., Taimre, T. and Vaisman, R.
  https://doi.org/10.36334/modsim.2023.menesch

Mengersen, K.
- Spatial autoregressive model for a Dirichlet distribution
  Nguyen, T., Moka, S., Mengersen, K. and Liquet, B.
  https://doi.org/10.36334/modsim.2023.nguyen242

Merrin, L.
- Hydrological connectivity patterns: Assessing the potential impact of water resource development on northern Australian wetlands
  Merrin, L.
  https://doi.org/10.36334/modsim.2023.merrin
- Modelling habitat suitability under hydrological change in aquatic habitats of northern Australia
  Stratford, D., Linke, S., Merrin, L., Lachish, S., Karim, F. and Kim, S.S.H.
  https://doi.org/10.36334/modsim.2023.stratford

Merritt, W.S.
- Using participatory foresight processes for strategic water management in Queensland
  Merritt, W.S., Fu, B., Rosello, C., Hamilton, S.H. and Riches, J.
  https://doi.org/10.36334/modsim.2023.merritt
- 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
- Making modelling socially inclusive: Mission possible?
  Hamilton, S.H., Merritt, W.S., Cosijn, M. and Carter, L.
  https://doi.org/10.36334/modsim.2023.hamilton648

Metcalfe, A.V.
- Change detection in drill core images based on local binary pattern
  Gu, X., Cook, N.J., Metcalfe, A.V. and Aldrich, C.
  https://doi.org/10.36334/modsim.2023.gu67
- Texture feature extraction for change detection in drill core images: A comparative study
  Gu, X., Cook, N.J., Metcalfe, A.V. and Aldrich, C.
  https://doi.org/10.36334/modsim.2023.gu69

Middleton, J.
- Improving access and efficiency in care delivery for patients with spinal cord injury in NSW Australia: A discrete-event dynamic simulation modelling approach
  Assareh, H., Pavlov, V., Adarkar, K., Johnson, J., Fortunato, R., Marial, O. and Middleton, J.
  https://doi.org/10.36334/modsim.2023.assareh

Miller, D.
- A novel application of multilevel SEM: Teaching quality as mediator between intervention and student achievement
  Tian, R., Stojanovski, E. and Miller, D.
  https://doi.org/10.36334/modsim.2023.tian126

Miller, D.G.
- Cross-scale analysis of social-ecological systems: Policy options appraisal for delivering NetZero and other environmental objectives in Scotland
  Matthews, K.B., Blackstock, K.L., Wardell-Johnson, D.H., Miller, D.G., Tavana, M., Thomson, S., Moxey, A., Nielsen, R., Baggaley, N., Loades, K., Paterson, E., Pakeman, R., Hawes, C., Stockan, J., Stutter, M., Addy, S. and Wilkinson, M.
  https://doi.org/10.36334/modsim.2023.matthews

Miller, S.M.
- A strategic planning model for the operation plan in lamb supply chains
  Wang, G., Costa, A., Karunarathne, W., Roughan, M., Miller, S.M. and Pitchford, W.
  https://doi.org/10.36334/modsim.2023.wang57

Miller, W.
- An optimised strategy for using cooperating missiles for missile defence
  Kapsis, M., Pudney, P., Miller, W. and Freebairn, G.
  https://doi.org/10.36334/modsim.2023.kapsis100
- Determining the best type of defending missile for cooperative missile defence
  Kapsis, M., Pudney, P., Miller, W. and Freebairn, G.
  https://doi.org/10.36334/modsim.2023.kapsis84

Minaudo, C.
- Australia’s water quality trends over two decades
  Guo, D., Minaudo, C., Zhang, Q., Dupas, R., Liu, S., Zhang, K., Bende-Michl, U., Duvert, C. and Lintern, A.
  https://doi.org/10.36334/modsim.2023.guo615

Miotlinski, K.
- Predicting impact of fires on water quality
  Miotlinski, K., Horwitz, P., Bellhouse, J.A., Blake, D., Silberstein, R., Bath, A., Mitchell, A., Carvalho, A. and Tshering, K.
  https://doi.org/10.36334/modsim.2023.miotlinski

Mirza, F.
- Provena: A provenance system for large distributed modelling and simulation workflows
  Yu, J., Baker, P., Cox, S.J.D., Petridis, R., Freebairn, A.C., Mirza, F., Thomas, L., Tickell, S., Lemon, D. and Rezvani, M.
  https://doi.org/10.36334/modsim.2023.yu90

Mishra, U.
- A framework for the fusion of earth observation and soil data to constrain soil organic carbon model parameters
  Ugbaje, S.U., Pagendam, D.E., Karunaratne, S., Bishop, T., Mishra, U., Gautam, S. and Farrell, M.
  https://doi.org/10.36334/modsim.2023.ugbaje

Mitchell, A.
- Predicting impact of fires on water quality
  Miotlinski, K., Horwitz, P., Bellhouse, J.A., Blake, D., Silberstein, R., Bath, A., Mitchell, A., Carvalho, A. and Tshering, K.
  https://doi.org/10.36334/modsim.2023.miotlinski

Mitchell, P.
- Long-range impact-based forecasts for agricultural drought early warning in Australia
  Schepen, A., Hughes, N., Gaydon, D., Sharman, C., McComb, J., Mitchell, P. and Carter, J.
  https://doi.org/10.36334/modsim.2023.schepen

Mo, J.
- Modelling the future trend of the citrus gall wasp population in southern Australia
  Mo, J.
  https://doi.org/10.36334/modsim.2023.mo

Moallemi, E.A.
- Systems modelling for sustainability transitions: Virtues and vices
  Moallemi, E.A.
  https://doi.org/10.36334/modsim.2023.moallemi
- Socio-ecological system dynamics modelling for sustainability assessment at the local scale
  Szetey, K., Moallemi, E.A. and Bryan, B.A.
  https://doi.org/10.36334/modsim.2023.szetey

Modecki, K.
- Multiverse experiments for enhancing reproducibility and resilience of statistical modelling via case studies in family wellbeing and biodiversity conservation
  Low-Choy, S., Modecki, K., Vasco, D., Alkhairy, I. and Hallgren, W.
  https://doi.org/10.36334/modsim.2023.lowchoy654

Moinuddin, K.
- Validation of FDS for simulating merging fires
  Wadhwani, R., Sutherland, D., Moinuddin, K. and Huang, X.
  https://doi.org/10.36334/modsim.2023.wadhwani
- Physics-based modelling of junction fires: Effects of some topographical parameters in intersecting fires
  Hassan, A., Accary, G., Sutherland, D. and Moinuddin, K.
  https://doi.org/10.36334/modsim.2023.hassan
- Development of a firebrand landing model based on CFD simulation
  Kyng, M., Moinuddin, K. and Hilton, J.
  https://doi.org/10.36334/modsim.2023.kyng

Moka, S.
- Efficient rare event simulation for random graphs via importance sampling
  Moka, S.
  https://doi.org/10.36334/modsim.2023.moka
- A continuous optimization algorithm for column subset selection
  Mathur, A., Moka, S. and Botev, Z.
  https://doi.org/10.36334/modsim.2023.mathur
- Spatial autoregressive model for a Dirichlet distribution
  Nguyen, T., Moka, S., Mengersen, K. and Liquet, B.
  https://doi.org/10.36334/modsim.2023.nguyen242

Mokany, K.
- 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

Mondal, A.
- Can drought regimes undergo shifts?
  Goswami, P., Peterson, T.J., Mondal, A. and Rüdiger, C.
  https://doi.org/10.36334/modsim.2023.goswami501

Mongin, M.
- Simulated deposition of aeolian dust on the Australian continental shelf: Preliminary results
  Margvelashvili, N., Skerratt, J.H., Mongin, M., Baird, M.E. and Wild-Allen, K.
  https://doi.org/10.36334/modsim.2023.margvelashvili
- Integrating field observations and mapping with model outputs (pesticides) to help identify ecologically vulnerable areas and determine suitable field site locations in the Great Barrier Reef
  Skerratt, J.H., Baird, M.E. and Mongin, M.
  https://doi.org/10.36334/modsim.2023.skerratt
- Using deep learning methods to create translators between biogeochemical models, improving regional ocean model global integration
  Mongin, M., Phillips, L., Frydman, S. and Jones, E.
  https://doi.org/10.36334/modsim.2023.mongin

Monsalve-Bravo, G.M.
- Mathematical modelling demonstrates how students can get stuck in unproductive learning regimes
  Egger, F., Lodge, J.M., Adams, M.P., Birkett, G.R., Monsalve-Bravo, G.M., Howes, T. and O'Brien, K.R.
  https://doi.org/10.36334/modsim.2023.egger512

Montazeri, M.
- Hydrodynamic and hydrological modelling to assess benefits, risks, and trade-offs from engineered flooding with a limited water resource
  Montazeri, M., McCullough, D.P. and Gibbs, M.S.
  https://doi.org/10.36334/modsim.2023.montazeri

Moolman, J.
- Functionalities in eWater Source to address new challenges in hydrological modelling
  Nair, S., Moolman, J., Li, Y. and McCallum, S.
  https://doi.org/10.36334/modsim.2023.nair

Moore, C.
- 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

Moss, J.
- An agent-based model for sustainable agricultural development in the Upper Mekong Delta of Vietnam
  Le, T.H.L., Welch, M.C., Moss, J., Vo, B. and Kristiansen, P.
  https://doi.org/10.36334/modsim.2023.le570

Moxey, A.
- Cross-scale analysis of social-ecological systems: Policy options appraisal for delivering NetZero and other environmental objectives in Scotland
  Matthews, K.B., Blackstock, K.L., Wardell-Johnson, D.H., Miller, D.G., Tavana, M., Thomson, S., Moxey, A., Nielsen, R., Baggaley, N., Loades, K., Paterson, E., Pakeman, R., Hawes, C., Stockan, J., Stutter, M., Addy, S. and Wilkinson, M.
  https://doi.org/10.36334/modsim.2023.matthews

Muirhead, R.W.
- 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

Mukai, N.
- Japanese flower arrangement simulator considering deterioration of flowers
  Mukai, N., Yanagisawa, M. and Chang, Y.
  https://doi.org/10.36334/modsim.2023.mukai

Müller, W.
- 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

Murphy, A.
- Mapping the interactions that drive the collective motion of soccer players during gameplay
  Welch, M.C., Schaerf, T.M. and Murphy, A.
  https://doi.org/10.36334/modsim.2023.welch466

Murphy, S.R.
- A method to improve the efficiency of calibrating biophysical models for pastures
  Thomas, D.T., Chen, C., Ota, N., Mata, G., Murphy, S.R., Giblin, S. and Beale, P.J.
  https://doi.org/10.36334/modsim.2023.thomas105

Murray, H.S.
- Optimisation of list management in the Australian Football League using deterministic methods
  Murray, H.S.
  https://doi.org/10.36334/modsim.2023.murray

Mushunje, L.
- GANs through the looking glass: How real is the fake financial data created by Generative Adversarial Neural Nets?
  Allen, D.E., Mushunje, L. and Peiris, S.
  https://doi.org/10.36334/modsim.2023.allen

Muylaert, R.L.
- Mapping the risk of disease transmission between wild bovids and domestic livestock in Thailand
  Horpiencharoen, W., Marshall, J., Muylaert, R.L., John, R.S. and Hayman, D.T.S.
  https://doi.org/10.36334/modsim.2023.horpiencharoen

Myers, T.
- Strategic decisions for routing autonomous vehicles: When to reoptimise?
  Andersen, T., Sankupellay, M., Belward, S., Myers, T. and Chen, C.
  https://doi.org/10.36334/modsim.2023.andersen

Modelling to support planning for resilience in a changing world