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

Saco, P.M.
- Hydrodynamic influence on vegetation establishment and biomass storage in coastal wetland systems
  Sandi, S.G., Rodríguez, J.F., Saco, P.M. and Saintilan, N.
  https://doi.org/10.36334/modsim.2023.sandi
- Assessment of mangroves' resilience to land use and climate change in the Pacific Islands
  Jorquera, E., Quijano Baron, J.P., Breda, A., Sandi, S.G., Verdon-Kidd, D., Saco, P.M. and Rodríguez, J.F.
  https://doi.org/10.36334/modsim.2023.jorquera
- Ecohydrological interactions in coastal wetlands and their resilience to future sea-level rise
  Saco, P.M., Rodríguez, J.F., Breda, A. and Sandi, S.G.
  https://doi.org/10.36334/modsim.2023.saco
- 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
- NDVI and accumulated antecedent precipitation in the drylands of Mendoza, Argentina
  Brieva, C., Saco, P.M., Rodríguez, J.F. and Sandi, S.G.
  https://doi.org/10.36334/modsim.2023.brieva

Sadegh Zadeh, H.
- A data-driven preventive surgery scheduling in flexible operating rooms using stochastic optimization
  Sadegh Zadeh, H., Anjomshoa, H., Zhang, L. and Fackrell, M.
  https://doi.org/10.36334/modsim.2023.sadeghzadeh

Saengtabtim, K.
- 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

Saft, M.
- Variable storage capacity in hydrological models to enhance performance under contrasting climates
  Trotter, L., Saft, M., Peel, M.C. and Fowler, K.J.A.
  https://doi.org/10.36334/modsim.2023.trotter
- What affects precipitation partitioning on interannual to interdecadal timescale?
  Saft, M. and Peel, M.C.
  https://doi.org/10.36334/modsim.2023.saft
- Do vegetation changes necessarily intensify hydrological shifts under multiyear droughts?
  Weligamage, H.A.C.G., Fowler, K.J.A., Saft, M., Ryu, D., Peterson, T.J. and Peel, M.C.
  https://doi.org/10.36334/modsim.2023.weligamage

Safwat, N.
- Identifying document relevance to Sustainable Development Goals using NLG
  Erechtchoukova, M.G. and Safwat, N.
  https://doi.org/10.36334/modsim.2023.erechtchoukova

Sağlam, Y.
- Developing an integrated socioeconomic-hydrological model to support catchment-scale water allocation decisions
  Rajanayaka, C., Sağlam, Y., Yang, J., Kees, L. and De Alwis, D.
  https://doi.org/10.36334/modsim.2023.rajanayaka

Sahin, O.
- Assuring rare earth mineral supply: A literature review and a systems model
  Sahin, O., Elsawah, S., Salim, H., Prior, D.D., Turan, H.H. and Hussain, O.K.
  https://doi.org/10.36334/modsim.2023.sahin

Saintilan, N.
- Hydrodynamic influence on vegetation establishment and biomass storage in coastal wetland systems
  Sandi, S.G., Rodríguez, J.F., Saco, P.M. and Saintilan, N.
  https://doi.org/10.36334/modsim.2023.sandi

Salazar, J.Z.
- "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
- Evaluating multiobjective evolutionary algorithms: A real-world benchmarking framework
  Salazar, J.Z., Hadka, D., Reed, P.M., Seada, H. and Deb, K.
  https://doi.org/10.36334/modsim.2023.salazar

Salim, H.
- Assuring rare earth mineral supply: A literature review and a systems model
  Sahin, O., Elsawah, S., Salim, H., Prior, D.D., Turan, H.H. and Hussain, O.K.
  https://doi.org/10.36334/modsim.2023.sahin

Salinas, H.
- Plant root architecture: A trade-off between tolerance to competitors and potential growth
  Salinas, H., Veneklaas, E., Poot, P., Trevenen, E. and Renton, M.
  https://doi.org/10.36334/modsim.2023.salinas

Samarasinghe, S.
- Using ensemble learning to analyse hurricane images to identify damage
  Kumara Pathirana, K.P.S.D, Kulasiri, D. and Samarasinghe, S.
  https://doi.org/10.36334/modsim.2023.kumarapathirana

Sampson, K.
- Influence of lateral flow on land surface fluxes in southeast Australia
  Devanand, A., Evans, J.P., Pitman, A.J., Pal, S., Gochis, D. and Sampson, K.
  https://doi.org/10.36334/modsim.2023.devanand397

San José, R.
- Air quality impacts forecasting system for industrial air emissions running in operational mode
  San José, R. and Perez-Camanyo, J.L.
  https://doi.org/10.36334/modsim.2023.sanjose

Sanches, V.H.
- 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

Sandi, S.G.
- Hydrodynamic influence on vegetation establishment and biomass storage in coastal wetland systems
  Sandi, S.G., Rodríguez, J.F., Saco, P.M. and Saintilan, N.
  https://doi.org/10.36334/modsim.2023.sandi
- Ecohydrological interactions in coastal wetlands and their resilience to future sea-level rise
  Saco, P.M., Rodríguez, J.F., Breda, A. and Sandi, S.G.
  https://doi.org/10.36334/modsim.2023.saco
- Assessment of mangroves' resilience to land use and climate change in the Pacific Islands
  Jorquera, E., Quijano Baron, J.P., Breda, A., Sandi, S.G., Verdon-Kidd, D., Saco, P.M. and Rodríguez, J.F.
  https://doi.org/10.36334/modsim.2023.jorquera
- 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
- NDVI and accumulated antecedent precipitation in the drylands of Mendoza, Argentina
  Brieva, C., Saco, P.M., Rodríguez, J.F. and Sandi, S.G.
  https://doi.org/10.36334/modsim.2023.brieva

Sankupellay, M.
- 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

Sargent, R.
- 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
- 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

Saurav, T.M.
- A computational framework for phenomenological modelling of ember storms at the wildland-urban interface
  Saurav, T.M., Sutherland, D. and Sharples, J.J.
  https://doi.org/10.36334/modsim.2023.saurav

Savadamuthu, K.
- Modelling flows from the past to inform flows for the future
  Penney, D., Savadamuthu, K., Van Der Wielen, M. and Gutiérrez-Jurado, K.Y.
  https://doi.org/10.36334/modsim.2023.penney
- 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

Savage, C.
- 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

Schaerf, T.M.
- A basic machine learning method for identifying individual biological state and ecological context from movement data
  Schaerf, T.M., Zvezdin, A.V., Welch, M.C., Wilson, A. and Ward, A.
  https://doi.org/10.36334/modsim.2023.schaerf
- Individual measures for heterogeneous collective motion
  Zvezdin, A.V., Welch, M.C. and Schaerf, T.M.
  https://doi.org/10.36334/modsim.2023.zvezdin
- 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
- Modelling collective states and individual-level interactions in small sheep flocks
  Welch, M.C., Alzubaidi, S. and Schaerf, T.M.
  https://doi.org/10.36334/modsim.2023.welch468

Schang, C.
- 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

Schepen, A.
- 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
- Better accounting of droughts in long-range inflow predictions with TULIP
  Horsley, D., Bennett, J.C., Schepen, A. and Robertson, D.E.
  https://doi.org/10.36334/modsim.2023.horsley
- 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

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

Schopf, J.
- 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
- Applying the Bureau of Meteorology’s national hydrological projections dataset to assess risks to future water supply scheme reliability
  Bellhouse, J.A., Schopf, J. and Turner, M.
  https://doi.org/10.36334/modsim.2023.bellhouse

Schreider, M.
- Algal bloom modelling based on satellite data
  Podsosonnaya, M., Schreider, M. and Schreider, S.
  https://doi.org/10.36334/modsim.2023.podsosonnaya

Schreider, S.
- Algal bloom modelling based on satellite data
  Podsosonnaya, M., Schreider, M. and Schreider, S.
  https://doi.org/10.36334/modsim.2023.podsosonnaya

Schroeder, T.
- 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

Schull, D.
- 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

Schulz, R.
- An application of machine learning in real estate economics: What extra benefits could machine learning techniques provide?
  Chan, F., Schulz, R. and Zhang, Z.
  https://doi.org/10.36334/modsim.2023.chan39

Schutt, A.
- Movement analytics in plant simulation software Tecnomatix
  Schutt, A., Smith, D.V. and Kapoor, R.
  https://doi.org/10.36334/modsim.2023.schutt

Schwenke, A.
- 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

Schwenke, G.D.
- 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

Scorah, M.
- 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
- 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

Scott, C.
- Leveraging high-performance computing facilities for the SWAT water quality catchment model
  Elliott, S., Hoang, L., Dang, T.D., Pletzer, A. and Scott, C.
  https://doi.org/10.36334/modsim.2023.elliott

Seada, H.
- Evaluating multiobjective evolutionary algorithms: A real-world benchmarking framework
  Salazar, J.Z., Hadka, D., Reed, P.M., Seada, H. and Deb, K.
  https://doi.org/10.36334/modsim.2023.salazar

Seaton, S.P.
- Design and implementation of a software tool supporting the Inter-Provincial Water Apportionment Accord in Pakistan
  Perraud, J.-M., Freebairn, A.C., Seaton, S.P., Yu, Y., Podger, G.M., Ahmad, M.D. and Cuddy, S.M.
  https://doi.org/10.36334/modsim.2023.perraud130

Seccull, C.
- Water supply modelling in a water-stressed remote community
  Holden, R. and Seccull, C.
  https://doi.org/10.36334/modsim.2023.holden

Sellers, E.
- 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

Sengupta, A.
- 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
- 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

Seo, L.
- Digital twin–based river-system model
  Seo, L., Branchaud, D., Petheram, C. and Watson, I.
  https://doi.org/10.36334/modsim.2023.seo610
- Regionalisation of rainfall-runoff models in southern and northern Australian catchments
  Seo, L., Hughes, J.D. and Petheram, C.
  https://doi.org/10.36334/modsim.2023.seo527
- Advancing environmental management through digital twin technology: A demonstration and future outlook for land and water resource development in Australia
  Branchaud, D., Seo, L., Petheram, C., Fu, Q. and Watson, I.
  https://doi.org/10.36334/modsim.2023.branchaud

Sexton, J.
- 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

Shanafield, M.
- 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

Shanthirathna, N.
- Performance persistence of socially responsible investment funds
  Shanthirathna, N., Gan, C., Vatsa, P. and Ho, L.T.
  https://doi.org/10.36334/modsim.2023.shanthirathna

Shao, Q.
- Uncertainty and its propagation estimation for an integrated water system model: An experiment from water quantity to quality simulations
  Zhang, Y. and Shao, Q.
  https://doi.org/10.36334/modsim.2023.zhang180
- 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

Shao, X.M.
- 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
- 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

Sharifazari, S.
- Resolving temporal-scale differences between paleoclimate reconstructions and a groundwater model for recharge estimation
  Sharifazari, S., Andersen, M.S., Johnson, F.M., Palmer, J.G. and Turney, C.S.M.
  https://doi.org/10.36334/modsim.2023.sharifazari

Sharma, A.
- 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
- Can annual streamflow volumes be characterised by flood events alone?
  Dykman, C., Sharma, A., Wasko, C. and Nathan, R.
  https://doi.org/10.36334/modsim.2023.dykman
- 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
- Catchment dynamics under climate change and the impact on rainfall losses and flooding
  Ho, M., Wasko, C., O'Shea, D., Nathan, R., Vogel, E. and Sharma, A.
  https://doi.org/10.36334/modsim.2023.ho272
- Improved rainfall frequency analysis through separation of storm intensity and storm arrival frequency
  O'Shea, D., Nathan, R., Sharma, A. and Wasko, C.
  https://doi.org/10.36334/modsim.2023.oshea
- Modelling future gross primary productivity in Australia
  Zou, H., Marshall, L.A. and Sharma, A.
  https://doi.org/10.36334/modsim.2023.zou336

Sharman, C.
- 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

Sharp, J.
- Use of SCRUM-APSIM to predict soil water and soil nitrogen dynamics in arable crop rotations
  Khaembah, E.N., Thomas, S., Cichota, R., Sharp, J. and Brown, H.
  https://doi.org/10.36334/modsim.2023.khaembah

Sharpee, T.
- 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

Sharples, J.J.
- A computational framework for phenomenological modelling of ember storms at the wildland-urban interface
  Saurav, T.M., Sutherland, D. and Sharples, J.J.
  https://doi.org/10.36334/modsim.2023.saurav
- An investigation of the heating, drying, and pyrolysis process of two separate moisturized cellulosic leaves
  Edalati-nejad, A., Ghodrat, M. and Sharples, J.J.
  https://doi.org/10.36334/modsim.2023.edalatinejad
- 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

Sharples, W.
- Streamflow regime shifts in a changing climate: A case study from Victoria, Australia
  Bende-Michl, U., Thomas, S., Bahramian, K., Kociuba, G., Sharples, W., Pepler, A. and Tolhurst, G.
  https://doi.org/10.36334/modsim.2023.bende-michl
- 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
- Improving seasonal streamflow calibration through consideration of raw ensemble spread
  Graham, T.D.J., Wang, Q.J., Pickett-Heaps, C.A., Sharples, W., Wu, W. and Western, A.W.
  https://doi.org/10.36334/modsim.2023.graham171
- What is the flood risk in Australia under future climate?
  Khan, Z., Bende-Michl, U., Srikanthan, S., Vogel, E., Sharples, W., Peter, J., Hope, P., Dowdy, A. and Wilson, L.
  https://doi.org/10.36334/modsim.2023.khan432
- 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

Shaw, M.
- 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

Shaygan, M.
- 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

Shen, S.
- A Bayesian change-point approach to nanopore basecalling
  Shen, S. and Sofronov, G.
  https://doi.org/10.36334/modsim.2023.shen

Sheng, M.S.
- 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

Shepherd, N.
- 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

Sheridan, G.
- 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

Shi, H.
- A thermal infrared imaging observation system for the measurement of overland flow velocities
  Shi, H., Shui, J. and Yang, X.
  https://doi.org/10.36334/modsim.2023.shi506
- 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

Shi, X.
- Spatiotemporal variation of water resources system vulnerability in the Upper Yangtze River, China
  Zhang, F., Wang, L., Shi, X., Zeng, C., Ahmad, I., Wang, G., Thapa, S. and Xu, X.
  https://doi.org/10.36334/modsim.2023.zhang394

Shin, S.-H.
- Systematic analysis and modeling for safety control in building demolition: A case study in South Korea
  Jeong, H.-J., Won, J.-H. and Shin, S.-H.
  https://doi.org/10.36334/modsim.2023.jeong
- NLP-based predictive model for identifying and presenting construction accident scenarios
  Shin, S.-H., Won, J.-H., Kim, G. and Jeong, H.-J.
  https://doi.org/10.36334/modsim.2023.shin436

Shinkai, K.
- Sequence analysis applying fuzzy graph theory and fuzzy core index method in social network analysis II
  Shinkai, K., Kanagawa, S. and Namekawa, M.
  https://doi.org/10.36334/modsim.2023.shinkai
- Optimal historical volatility for the Dow-Jones industrial average and its application
  Kanagawa, S., Namekawa, M. and Shinkai, K.
  https://doi.org/10.36334/modsim.2023.kanagawa

Shokri, A.
- Understanding river system sensitivity to climate variation
  Shokri, A., Robertson, D.E., Freebairn, A.C. and Potter, N.
  https://doi.org/10.36334/modsim.2023.shokri

Shrestha, D.L.
- Understanding residual risks of forecast-informed river system operations
  Robertson, D.E., Ng, T.L., Shrestha, D.L. and Bennett, J.C.
  https://doi.org/10.36334/modsim.2023.robertson
- Predicting flood inundation extent using remote sensing and machine learning techniques
  Shrestha, D.L., Robertson, D.E., Jin, W. and Ticehurst, C.
  https://doi.org/10.36334/modsim.2023.shrestha

Shui, J.
- A thermal infrared imaging observation system for the measurement of overland flow velocities
  Shi, H., Shui, J. and Yang, X.
  https://doi.org/10.36334/modsim.2023.shi506

Sibanda, T.
- Infectious disease spread in free-range egg-laying hens based on empirical mobility patterns and contact networks
  Palmini, A., Jarynowski, A., Welch, M.C., Belik, V., Sibanda, T. and Ruhnke, I.
  https://doi.org/10.36334/modsim.2023.palmini

Siddell, J.P.
- 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

Sidhu, H.
- Modelling of the activated sludge process with a stratified settling unit
  Watt, S., Nelson, M., Hai, F. and Sidhu, H.
  https://doi.org/10.36334/modsim.2023.watt

Silberstein, R.
- 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

Silburn, D.M.
- Calculating pesticide half-lives in reservoirs for model parameterisation
  Waters, D.K. and Silburn, D.M.
  https://doi.org/10.36334/modsim.2023.waters

Silva, S.S.M.
- Dynamic health status monitoring using aged care quality indicators for better care: An innovative approach using mixture hidden Markov models
  Silva, S.S.M., Wabe, N. and Westbrook, J.I.
  https://doi.org/10.36334/modsim.2023.silva

Simeoni, A.
- Effect of wind speed on wildfire interaction with multiple structures in the wildland–urban interface
  Ghodrat, M., Edalati-nejad, A. and Simeoni, A.
  https://doi.org/10.36334/modsim.2023.ghodrat136

Simmons, C.T.
- 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
- Increasing our understanding of the adjoint state method of model sensitivity calculation
  Turnadge, C., Neupauer, R.M., Batelaan, O., Crosbie, R.S. and Simmons, C.T.
  https://doi.org/10.36334/modsim.2023.turnadge

Simmons, J.
- Disentangling hydrological mixtures
  Athukorala, R., Simmons, J., Cripps, S. and Vervoort, R.W.
  https://doi.org/10.36334/modsim.2023.athukorala550
- Framework for interpretable Bayesian soil moisture modelling
  Simmons, J., Pino, V., Graaf, A. and Vervoort, R.W.
  https://doi.org/10.36334/modsim.2023.simmons461
- A time-varying parameter approach to quantifying rating curve changes
  Simmons, J., Vervoort, R.W. and Kohn, R.
  https://doi.org/10.36334/modsim.2023.simmons455

Simons, M.
- Ecohydrological option analysis for New South Wales’ coastal regional water strategies: Bega River
  Driver, P.D., Dutta, D., Delagarza, D. and Simons, M.
  https://doi.org/10.36334/modsim.2023.driver148

Simpson, A.R.
- Impact of search space discretisation on water distribution system design optimisation
  Zhao, Q., Wu, W., Simpson, A.R. and Willis, A.
  https://doi.org/10.36334/modsim.2023.zhao107
- Is behind-the-meter solar an effective way to improve water distribution system resilience?
  Yao, J., Wu, W., Simpson, A.R. and Rismanchi, B.
  https://doi.org/10.36334/modsim.2023.yao238

Simpson, J.
- 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
- Investigating an extreme drought event with the Bega River System Model
  Simpson, J., Han, X., Dutta, D., Purtle, C. and Craig, A.
  https://doi.org/10.36334/modsim.2023.simpson518

Sims, C.
- Black ooze and algae: Modelling the response and restoration of the Coorong
  Sims, C., Hipsey, M.R., Huang, P., Paraska, D. and Zhai, S.
  https://doi.org/10.36334/modsim.2023.sims
- Collaborative approach to developing an information management system for water resource models
  Finger, M., Sims, C. and Thomas, R.
  https://doi.org/10.36334/modsim.2023.finger

Singh, A.
- A model framework to predict pesticide concentrations in runoff at improved temporal and spatial resolution
  Singh, A. and Hipsey, M.R.
  https://doi.org/10.36334/modsim.2023.singh141
- Parameter sensitivity analysis of the MERGE quasi-steady state gully erosion model
  Bennett, F.R., Singh, A. and Roberts, M.E.
  https://doi.org/10.36334/modsim.2023.bennett128
- Developing an assessment framework to guide investment in water models
  Gibbes, B., Botelho, D., Singh, A., Rissik, D. and Hipsey, M.R.
  https://doi.org/10.36334/modsim.2023.gibbes

Singh, D.
- 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

Singh, K.P.
- Impact of distance to travel in cervical cancer outcome: National Cancer Database Study
  Bae, S., Pandya, V., Park, H., Wang, Z., Wang, C., Wang, H., Uhm, M., Huh, W. and Singh, K.P.
  https://doi.org/10.36334/modsim.2023.bae
- 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

Singh, P.
- 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

Singh, R.
- Machine learning and multinomal models: A simulation study
  Chan, F., Harris, M., Singh, R. and Yeo, W.
  https://doi.org/10.36334/modsim.2023.chan70
- Selecting the relevant forecasts for forecast combination
  Chan, F. and Singh, R.
  https://doi.org/10.36334/modsim.2023.chan151
- Use of APSIM Next Generation to identify in-field practices to reduce N leaching under intensive vegetable production systems
  Avendano, F., Cichota, R., Horne, D., Singh, R., Palmer, A. and Bloomer, D.
  https://doi.org/10.36334/modsim.2023.avendano334

Sinnott, M.D.
- Challenges of developing a digital twin of an in-vitro device that mimics swallowing
  Ghosh, S., Sinnott, M.D., Cleary, P.W., Harrison, S.M. and Stading, M.
  https://doi.org/10.36334/modsim.2023.ghosh146

Sivakumar, B.
- A comprehensive study of high frequency temporal chaotic behavior of riverine water quality dynamics
  Zhu, M., Jiang, J.P., Tang, S. and Sivakumar, B.
  https://doi.org/10.36334/modsim.2023.zhu640

Skerratt, J.H.
- 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

Smith, C.
- Sampling NARCliM factored stochastic data for infrastructure risk assessment
  Beecham, R., Smith, C., Sugiyanto, M., Dutta, D. and Armstrong, M.
  https://doi.org/10.36334/modsim.2023.beecham

Smith, D.V.
- Movement analytics in plant simulation software Tecnomatix
  Schutt, A., Smith, D.V. and Kapoor, R.
  https://doi.org/10.36334/modsim.2023.schutt
- Indoor movement data analytics based on machine learning for manufacturing assembly line
  Rana, M., Smith, D.V., Rahman, A. and Baumgartner, P.
  https://doi.org/10.36334/modsim.2023.rana

Smith-Miles, K.
- Explainable algorithm evaluation from lessons in education
  Kandanaarachchi, S. and Smith-Miles, K.
  https://doi.org/10.36334/modsim.2023.kandanaarachchi202

Smolders, K.
- Assessing algal bloom risks from purified recycled water addition to Lake Wivenhoe
  Yu, S., Hamilton, D.P., Okely, P., Smolders, K. and Burford, M.
  https://doi.org/10.36334/modsim.2023.yu532

Snow, V.
- 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

Sofronov, G.
- A binary segmentation method for detecting topological domains in Hi-C data
  Raveendran, N. and Sofronov, G.
  https://doi.org/10.36334/modsim.2023.raveendran
- A Bayesian change-point approach to nanopore basecalling
  Shen, S. and Sofronov, G.
  https://doi.org/10.36334/modsim.2023.shen

Sofronova, K.
- Statistical analysis of Australian insurance losses from historical catastrophic disasters
  Sofronova, K. and Raveendran, N.
  https://doi.org/10.36334/modsim.2023.sofronova

Soltyk, S.J.
- Combining risk forecasts
  Soltyk, S.J., Chan, F., Phatak, A. and Jackson, E.L.
  https://doi.org/10.36334/modsim.2023.soltyk

Somers, V.
- 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

Song, P.
- Fusion of all-weather and high-resolution satellite soil moisture data for better simulating evapotranspiration over China
  Song, P.
  https://doi.org/10.36334/modsim.2023.song680

Song, S.U.
- 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

Sornklin, B.
- 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

Spillias, S.
- Collaborative intelligence for modelling marine social-ecological systems
  Spillias, S.
  https://doi.org/10.36334/modsim.2023.spillias

Spratt, B.
- A comprehensive approach to operating theatre scheduling
  Humphreys, P., Spratt, B., Tariverdi, M., Hamilton, A., Cook, D., Burdett, R., Yarlagadda, P. and Corry, P.
  https://doi.org/10.36334/modsim.2023.humphreys

Srikanthan, S.
- What is the flood risk in Australia under future climate?
  Khan, Z., Bende-Michl, U., Srikanthan, S., Vogel, E., Sharples, W., Peter, J., Hope, P., Dowdy, A. and Wilson, L.
  https://doi.org/10.36334/modsim.2023.khan432

Staby, S.-E.
- Moving beyond attrition in modelling land combat
  Staby, S.-E., Blumson, D., Cao, T., Elsawah, S., Gary, M.S., Hock, K., Kosowski, L. and Richmond, M.K.
  https://doi.org/10.36334/modsim.2023.staby373
- 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
- Modelling process of complex problems from a teaching perspective
  Staby, S.-E. and Rios-Ocampo, J.P.
  https://doi.org/10.36334/modsim.2023.staby625

Stading, M.
- Challenges of developing a digital twin of an in-vitro device that mimics swallowing
  Ghosh, S., Sinnott, M.D., Cleary, P.W., Harrison, S.M. and Stading, M.
  https://doi.org/10.36334/modsim.2023.ghosh146

Stenborg, T.
- Adaptive MCMC parallelisation in Stan
  Stenborg, T.
  https://doi.org/10.36334/modsim.2023.stenborg

Stewardson, M.
- Assessing climate change impacts on dual-priority water rights in carryover systems at basin scale
  Ren, P., Stewardson, M., Peel, M.C., Turner, M. and John, A.
  https://doi.org/10.36334/modsim.2023.ren357
- The time of emergence of climate change in Australian rivers
  John, A., Nathan, R., Horne, A., Fowler, K.J.A., Stewardson, M., Peel, M.C. and Webb, J.A.
  https://doi.org/10.36334/modsim.2023.john
- A rapid analytical model to represent dual-priority water rights in carryover systems
  Ren, P., Stewardson, M. and Peel, M.C.
  https://doi.org/10.36334/modsim.2023.ren355

Stockan, J.
- 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

Stojanovski, E.
- 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
- A visual examination of Selikoff’s 20-year rule using correspondence analysis and the Cressie-Read family of divergence statistics
  Alzahrani, A., Beh, E.J. and Stojanovski, E.
  https://doi.org/10.36334/modsim.2023.alzahrani

Stokes, C.
- Linking hydrological and infrastructure models to evaluate the proposed Bradfield Scheme
  Petheram, C., Hughes, J.D., Read, A. and Stokes, C.
  https://doi.org/10.36334/modsim.2023.petheram

Stott, R.
- 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

Strahan, K.
- 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

Stratford, D.
- 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
- 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
- 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

Stutter, M.
- 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

Su, C.-H.
- 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

Sugiyanto, M.
- Sampling NARCliM factored stochastic data for infrastructure risk assessment
  Beecham, R., Smith, C., Sugiyanto, M., Dutta, D. and Armstrong, M.
  https://doi.org/10.36334/modsim.2023.beecham

Sukias, J.P.S.
- 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

Suleman, M.
- Seasonality clustering and trend analysis of meteorological data using hybrid approach
  Suleman, M. and Khaiter, P.
  https://doi.org/10.36334/modsim.2023.suleman

Sunter, P.
- 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

Sutherland, D.
- 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
- Validation of FDS for simulating merging fires
  Wadhwani, R., Sutherland, D., Moinuddin, K. and Huang, X.
  https://doi.org/10.36334/modsim.2023.wadhwani
- A computational framework for phenomenological modelling of ember storms at the wildland-urban interface
  Saurav, T.M., Sutherland, D. and Sharples, J.J.
  https://doi.org/10.36334/modsim.2023.saurav

Suzzi, A.L.
- '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

Swaffer, B.
- 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

Syktus, J.
- 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
- 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
- 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

Sysoeva, P.
- A hybrid approach to mountain forest management using Earth observing system and machine learning
  Sysoeva, P. and Khaiter, P.
  https://doi.org/10.36334/modsim.2023.sysoeva

Szetey, K.
- 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
- 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

Szilagyi, J.
- 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

Taghikhah, F.R.
- A conceptual framework for developing digital twins of human-environmental systems
  Taghikhah, F.R.
  https://doi.org/10.36334/modsim.2023.taghikhah

Tague, C.
- 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

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

Tait, A.
- 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

Tam, E.
- 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

Tan, C.W.
- Applications of convolutional neural networks and remote sensing data to predict flood extents
  Nguyen, C., Tan, C.W., Daly, E. and Pauwels, V.N.M.
  https://doi.org/10.36334/modsim.2023.nguyen328

Tan, D.
- Assessing the impact of open biomass burning on UK air quality
  Tan, D., Vieno, M., Nemitz, E., Heal, M. and Reis, S.
  https://doi.org/10.36334/modsim.2023.tan177
- 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

Tang, F.H.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

Tang, J.
- 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
- 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
- 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

Tang, S.
- A comprehensive study of high frequency temporal chaotic behavior of riverine water quality dynamics
  Zhu, M., Jiang, J.P., Tang, S. and Sivakumar, B.
  https://doi.org/10.36334/modsim.2023.zhu640

Tang, Y.
- Analysis of impact of catchment antecedent moisture conditions on runoff generations
  Tang, Y., Han, X., Cu, T.P. and Dutta, D.
  https://doi.org/10.36334/modsim.2023.tang300

Tang, Z.X.
- 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
- Simulating hydrological consequences of the 2022 severe drought in the Yangtze River Basin, China
  Tang, Z.X., Zhang, Y.Q. and Kong, D.D.
  https://doi.org/10.36334/modsim.2023.tang484

Tariverdi, M.
- A comprehensive approach to operating theatre scheduling
  Humphreys, P., Spratt, B., Tariverdi, M., Hamilton, A., Cook, D., Burdett, R., Yarlagadda, P. and Corry, P.
  https://doi.org/10.36334/modsim.2023.humphreys

Tartaglia, E.
- Data-driven probabilistic logic programming applied to movement analytics in manufacturing
  Tartaglia, E. and Baumgartner, P.
  https://doi.org/10.36334/modsim.2023.tartaglia

Tavana, M.
- 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

Taylor, A.R.
- Identifying potential groundwater discharge areas using remotely sensed evapotranspiration
  Crosbie, R.S., Taylor, A.R. and Pritchard, J.L.
  https://doi.org/10.36334/modsim.2023.crosbie361

Taylor, N.
- 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
- 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

Taylor, P.
- Engaging users in critical appraisal of computer model software
  Rosello, C., Guillaume, J.H.A., Taylor, P., Cuddy, S.M., Pollino, C.A. and Jakeman, A.J.
  https://doi.org/10.36334/modsim.2023.rosello628

Teixeira, D.
- 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

Teixeira, M.
- 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

Teng, J.
- 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
- 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
- Realised added value in rainfall trends and variance from regional climate models
  Teng, J., Bennett, J.C., Charles, S., Chiew, F.H.S., Ji, F., Potter, N., Fu, G. and Thatcher, M.
  https://doi.org/10.36334/modsim.2023.teng316
- 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

Tetreault-Campbell, S.
- 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
- 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

Thackway, R.
- 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

Thapa, S.
- Spatiotemporal variation of water resources system vulnerability in the Upper Yangtze River, China
  Zhang, F., Wang, L., Shi, X., Zeng, C., Ahmad, I., Wang, G., Thapa, S. and Xu, X.
  https://doi.org/10.36334/modsim.2023.zhang394

Thatcher, M.
- Realised added value in rainfall trends and variance from regional climate models
  Teng, J., Bennett, J.C., Charles, S., Chiew, F.H.S., Ji, F., Potter, N., Fu, G. and Thatcher, M.
  https://doi.org/10.36334/modsim.2023.teng316

Thomas, C.
- 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

Thomas, D.G.
- 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
- 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

Thomas, D.T.
- 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

Thomas, H.
- How ‘green’ is my hydrogen? A comparative study of land, water, and wastewater footprints of renewable hydrogen production
  Thomas, H., Bennett, D., Peeters, L.J.M. and Holland, K.
  https://doi.org/10.36334/modsim.2023.thomas391

Thomas, L.
- 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

Thomas, P.Q.
- 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

Thomas, R.
- Collaborative approach to developing an information management system for water resource models
  Finger, M., Sims, C. and Thomas, R.
  https://doi.org/10.36334/modsim.2023.finger

Thomas, S.
- 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
- Streamflow regime shifts in a changing climate: A case study from Victoria, Australia
  Bende-Michl, U., Thomas, S., Bahramian, K., Kociuba, G., Sharples, W., Pepler, A. and Tolhurst, G.
  https://doi.org/10.36334/modsim.2023.bende-michl
- Use of SCRUM-APSIM to predict soil water and soil nitrogen dynamics in arable crop rotations
  Khaembah, E.N., Thomas, S., Cichota, R., Sharp, J. and Brown, H.
  https://doi.org/10.36334/modsim.2023.khaembah

Thompson, J.
- 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
- 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

Thomson, R.
- An IoT digital twin to create Sydney’s coolest park
  Urich, C., Cressall, B., Pasanen, J., Obst, O., Javadi, B., Kocyigit, M., Thomson, R., Tovey, A., Owen, C. and Pfautsch, S.
  https://doi.org/10.36334/modsim.2023.urich

Thomson, S.
- 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

Thyer, M.
- 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

Tian, F.
- 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

Tian, J.
- 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
- 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
- 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
- Root zone soil moisture estimation over China
  Tian, J. and Zhang, Y.Q.
  https://doi.org/10.36334/modsim.2023.tian218
- 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

Tian, R.
- 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

Tian, S.
- 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

Ticehurst, C.
- 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
- 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
- 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
- Predicting flood inundation extent using remote sensing and machine learning techniques
  Shrestha, D.L., Robertson, D.E., Jin, W. and Ticehurst, C.
  https://doi.org/10.36334/modsim.2023.shrestha

Tickell, S.
- 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

Tiong, J.K.R.
- Markov chain modelling of causality in anomalous and non-anomalous combat event series
  Tiong, J.K.R., Bogomolov, T. and Chiera, B.A.
  https://doi.org/10.36334/modsim.2023.tiong

Tolhurst, G.
- Streamflow regime shifts in a changing climate: A case study from Victoria, Australia
  Bende-Michl, U., Thomas, S., Bahramian, K., Kociuba, G., Sharples, W., Pepler, A. and Tolhurst, G.
  https://doi.org/10.36334/modsim.2023.bende-michl

Tong, R.
- 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

Toohey, E.
- 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

Toombs, N.
- 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
- 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

Toscas, P.
- 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

Tovey, A.
- An IoT digital twin to create Sydney’s coolest park
  Urich, C., Cressall, B., Pasanen, J., Obst, O., Javadi, B., Kocyigit, M., Thomson, R., Tovey, A., Owen, C. and Pfautsch, S.
  https://doi.org/10.36334/modsim.2023.urich

Trancoso, R.
- 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
- 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
- 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
- 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

Tran-Duy, A.
- Simulating the impact of changes in combined risk factor levels on life expectancy in older individuals with type 1 diabetes
  Tran-Duy, A.
  https://doi.org/10.36334/modsim.2023.tranduy

Trevaskis, B.
- 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
- 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

Trevenen, E.
- Plant root architecture: A trade-off between tolerance to competitors and potential growth
  Salinas, H., Veneklaas, E., Poot, P., Trevenen, E. and Renton, M.
  https://doi.org/10.36334/modsim.2023.salinas

Trim, A.
- Modelling the Murray-Darling Basin Southern Connected System
  Trim, A., Podger, G.M., Dutta, D. and Puertas, J.M.
  https://doi.org/10.36334/modsim.2023.trim
- 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

Trotter, L.
- Variable storage capacity in hydrological models to enhance performance under contrasting climates
  Trotter, L., Saft, M., Peel, M.C. and Fowler, K.J.A.
  https://doi.org/10.36334/modsim.2023.trotter

Tseng, C.W.
- 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

Tshering, 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

Tsuchida, R.
- 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

Tuke, J.
- Predicting from functional brain images using partial least squares for Riemannian manifolds
  Ryan, M., Glonek, G., Tuke, J. and Humphries, M.
  https://doi.org/10.36334/modsim.2023.ryan

Turan, H.H.
- Assuring rare earth mineral supply: A literature review and a systems model
  Sahin, O., Elsawah, S., Salim, H., Prior, D.D., Turan, H.H. and Hussain, O.K.
  https://doi.org/10.36334/modsim.2023.sahin

Turnadge, C.
- 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
- Increasing our understanding of the adjoint state method of model sensitivity calculation
  Turnadge, C., Neupauer, R.M., Batelaan, O., Crosbie, R.S. and Simmons, C.T.
  https://doi.org/10.36334/modsim.2023.turnadge

Turner, M.
- Applying the Bureau of Meteorology’s national hydrological projections dataset to assess risks to future water supply scheme reliability
  Bellhouse, J.A., Schopf, J. and Turner, M.
  https://doi.org/10.36334/modsim.2023.bellhouse
- 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
- Assessing climate change impacts on dual-priority water rights in carryover systems at basin scale
  Ren, P., Stewardson, M., Peel, M.C., Turner, M. and John, A.
  https://doi.org/10.36334/modsim.2023.ren357

Turner, R.
- 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

Turney, C.S.M.
- Resolving temporal-scale differences between paleoclimate reconstructions and a groundwater model for recharge estimation
  Sharifazari, S., Andersen, M.S., Johnson, F.M., Palmer, J.G. and Turney, C.S.M.
  https://doi.org/10.36334/modsim.2023.sharifazari
- Past, present, and future droughts in the Murray–Darling Basin
  Higgins, P.A., Palmer, J.G., Andersen, M.S., Turney, C.S.M., Johnson, F.M., Allen, K., Verdon-Kidd, D. and Cook, E.R.
  https://doi.org/10.36334/modsim.2023.higgins559
- Bridging the data gap: A spatially resolved reconstruction of drought in the South Pacific Islands
  Higgins, P.A., Palmer, J.G., Andersen, M.S., Turney, C.S.M. and Johnson, F.M.
  https://doi.org/10.36334/modsim.2023.higgins276

Tuteja, N.
- The influence of different objective functions in GR4J model-on-model performance for streamflow forecasting application
  Nguyen, H., Tuteja, N., Perera, H., Raut, A., Hameed, T., Neupane, R. and Breda, A.
  https://doi.org/10.36334/modsim.2023.nguyen546
- Investigation of the sensitivity of weighting factor parameter in SDEB objective function
  Raut, A., Nguyen, H. and Tuteja, N.
  https://doi.org/10.36334/modsim.2023.raut

Tychsen-Smith, L.
- 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

Tyson, A.
- Estimates of recharge for current and future climate scenarios in Victoria using SoilFlux
  Jordan, P., Pinto, R., Tyson, A. and Fawcett, J.
  https://doi.org/10.36334/modsim.2023.jordan

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