Real-time prediction of the week-ahead flood index using hybrid deep learning algorithms with synoptic climate mode indices

Article


Ahmed, A.A. Masrur, Akther, Shahida, Nguyen-Huy, Thong, Raj, Nawin, Jui (Student), S Janifer and S.Z., Farzana. 2024. "Real-time prediction of the week-ahead flood index using hybrid deep learning algorithms with synoptic climate mode indices." Journal of Hydro-Environment Research. 57, pp. 12-26. https://doi.org/10.1016/j.jher.2024.09.001
Article Title

Real-time prediction of the week-ahead flood index using hybrid deep learning algorithms with synoptic climate mode indices

ERA Journal ID124541
Article CategoryArticle
AuthorsAhmed, A.A. Masrur, Akther, Shahida, Nguyen-Huy, Thong, Raj, Nawin, Jui (Student), S Janifer and S.Z., Farzana
Journal TitleJournal of Hydro-Environment Research
Journal Citation57, pp. 12-26
Number of Pages15
Year2024
PublisherElsevier
Place of PublicationNetherlands
ISSN1570-6443
1876-4444
Digital Object Identifier (DOI)https://doi.org/10.1016/j.jher.2024.09.001
Web Address (URL)https://www.sciencedirect.com/science/article/abs/pii/S1570644324000522
Abstract

This paper aims to propose a hybrid deep learning (DL) model that combines a convolutional neural network (CNN) with a bi-directional long-short term memory (BiLSTM) for week-ahead prediction of daily flood index (IF) for Bangladesh. The neighbourhood component analysis (NCA) is assigned for significant feature selection with synoptic-scale climatic indicators. The results successfully reveal that the hybrid CNN-BiLSTM model outperforms the respective benchmark models based on forecasting capability, as supported by a minimal mean absolute error and high-efficiency metrics. With respect to IF prediction, the hybrid CNN-BiLSTM model shows over 98% of the prediction errors were less than 0.015, resulting in a low relative error and superiority performance against the benchmark models in this study. The adaptability and potential utility of the suggested model may be helpful in subsequent flood monitoring and may also be beneficial to policymakers at the federal and state levels.

Keywordsflood index; Bangladesh; feature extraction; deep hybrid learning; climate indices
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020410199. Climate change impacts and adaptation not elsewhere classified
460207. Modelling and simulation
Public Notes

The accessible file is the submitted version of the paper. Please refer to the URL for the published version.

Byline AffiliationsDepartment of Climate Change, Energy, the Environment and Water, Canberra
School of Mathematics, Physics and Computing
Leading University, Bangladesh
Centre for Applied Climate Sciences
Thanh Do University, Vietnam
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Prediction of Sea Level with Vertical Land Movement Correction Using Deep Learning
Raj, Nawin. 2022. "Prediction of Sea Level with Vertical Land Movement Correction Using Deep Learning." Mathematics. 10 (23). https://doi.org/10.3390/math10234533
Drought outlook validation using ACCESS-S2 hindcast
Nguyen-Huy, Thong and Cobon, David. 2022. Drought outlook validation using ACCESS-S2 hindcast. Northern Australia Climate Program (NACP).
Systemic risk management in farming - geographic distribution and diversity
Nguyen-Huy, Thong. 2022. "Systemic risk management in farming - geographic distribution and diversity." Future Drought Fund’s 2022 Science to Practice Forum. 07 - 08 Jun 2022 Australia.
Development of Deep Learning Hybrid Models for Hydrological Predictions
Ahmed, Abul Abrar Masrur. 2022. Development of Deep Learning Hybrid Models for Hydrological Predictions. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/q7q5z
Australian Drought Monitor
Cobon, David, Gacenga, Francis, An-Vo, Duc-Anh, Pudmenzky, Christa, Nguyen-Huy, Thong, Stone, Roger, Guillory, Laura, McCulloch, J., Svoboda, M., Swigart, J. and Meat & Livestock Australia. 2022. Australian Drought Monitor. Toowoomba. https://doi.org/10.26192/dmek-v625
Support vector machine model for multistep wind speed forecasting
Prasad, Shobna Mohini Mala, Nguyen-Huy, Thong and Deo, Ravinesh. 2021. "Support vector machine model for multistep wind speed forecasting." Deo, Ravinesh, Samui, Pijush and Roy, Sanjiban Sekhar (ed.) Predictive modelling for energy management and power systems engineering. Netherlands. Elsevier. pp. 335-389
Development of data-driven models for wind speed forecasting in Australia
Neupane, Ananta, Raj, Nawin, Deo, Ravinesh and Ali, Mumtaz. 2021. "Development of data-driven models for wind speed forecasting in Australia." Deo, R., Samui, Pijush and Roy, Sanjiban Sekhar (ed.) Predictive modelling for energy management and power systems engineering. Netherlands. Elsevier. pp. 143-190
Guidance law for a surveillance UAV swarm tracking a high capability malicious UAV
Brown, Jason and Raj, Nawin. 2021. "Guidance law for a surveillance UAV swarm tracking a high capability malicious UAV." 2021 IEEE Asia Pacific Conference on Wireless and Mobile (APWiMob 2021). Bandung, Indonesia 08 - 10 Apr 2021 United States. https://doi.org/10.1109/APWiMob51111.2021.9435240
The Impact of Initial Swarm Formation for Tracking of a High Capability Malicious UAV
Brown, Jason and Raj, Nawin. 2021. "The Impact of Initial Swarm Formation for Tracking of a High Capability Malicious UAV." International IOT, Electronics and Mechatronics Conference (IEMTRONICS 2021). Toronto, Canada 21 - 24 Apr 2021 Piscataway, United States. https://doi.org/10.1109/IEMTRONICS52119.2021.9422506
Predictive Tracking of a High Capability Malicious UAV
Brown, Jason and Raj, Nawin. 2021. "Predictive Tracking of a High Capability Malicious UAV." IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC 2021). Las Vegas, United States 27 - 30 Jan 2021 Piscataway, United States. https://doi.org/10.1109/CCWC51732.2021.9376137
Evaluation of multivariate adaptive regression splines and artificial neural network for prediction of mean sea level trend around northern Australian coastlines
Raj, Nawin and Gharineiat, zahra. 2021. "Evaluation of multivariate adaptive regression splines and artificial neural network for prediction of mean sea level trend around northern Australian coastlines." Mathematics. 9 (21), pp. 1-20. https://doi.org/10.3390/math9212696
Novel short-term solar radiation hybrid model: long short-term memory network integrated with robust local mean decomposition
Huynh, Anh Ngoc-Lan, Deo, Ravinesh C., Ali, Mumtaz, Abdulla, Shahab and Raj, Nawin. 2021. "Novel short-term solar radiation hybrid model: long short-term memory network integrated with robust local mean decomposition." Applied Energy. 298, pp. 1-19. https://doi.org/10.1016/j.apenergy.2021.117193
Specifying the relationship between land use/land cover change and dryness in central Vietnam from 2000 to 2019 using Google Earth Engine
Pham, Thy T. M., Nguyen, The-Duoc, Tham, Han T. N., Truong, Thi Nhat Kieu, Lam-Dao, Nguyen and Nguyen-Huy, Thong. 2021. "Specifying the relationship between land use/land cover change and dryness in central Vietnam from 2000 to 2019 using Google Earth Engine." Journal of Applied Remote Sensing. 15 (2), pp. 1-21. https://doi.org/10.1117/1.JRS.15.024503
Hybrid deep learning method for a week-ahead evapotranspiration forecasting
Ahmed, A. A. Masrur, Deo, Ravinesh C., Feng, Qi, Ghahramani, Afshin, Raj, Nawin, Yin, Zhenliang and Yang, Linshan. 2022. "Hybrid deep learning method for a week-ahead evapotranspiration forecasting." Stochastic Environmental Research and Risk Assessment. 36 (3), pp. 831-849. https://doi.org/10.1007/s00477-021-02078-x
Particle and particle-like solitary wave dynamics in fluid media
Raj, Nawin. 2015. Particle and particle-like solitary wave dynamics in fluid media. PhD Thesis Doctor of Philosophy. University of Southern Queensland.
Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data
Ahmed, A. A. Masrur, Deo, Ravinesh C., Raj, Nawin, Ghahramani, Afshin, Feng, Qi, Yin, Zhenliang and Yang, Linshan. 2021. "Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data." Remote Sensing. 13 (4), pp. 1-30. https://doi.org/10.3390/rs13040554
Hydropower dams, river drought and health effects: a detection and attribution study in the lower Mekong Delta Region
Phung, Dung, Nguyen-Huy, Thong, Tran, Ngoc Nguyen, Tran, Dang Ngoc, Doan, Van Quang, Nghiem, Son, Nguyen, Nga Huy, Nguyen, Trung Hieu and Bennett, Trude. 2021. "Hydropower dams, river drought and health effects: a detection and attribution study in the lower Mekong Delta Region." Climate Risk Management. 32. https://doi.org/10.1016/j.crm.2021.100280
LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4.5 and RCP8.5 global warming scenarios
Ahmed, A. A. Masrur, Deo, Ravinesh C., Ghahramani, Afshin, Raj, Nawin, Feng, Qi, Yin, Zhenliang and Yang, Linshan. 2021. "LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4.5 and RCP8.5 global warming scenarios." Stochastic Environmental Research and Risk Assessment. 35, pp. 1851-1881. https://doi.org/10.1007/s00477-021-01969-3
Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity
Ahmed, A. A. Masrur, Deo, Ravinesh C., Feng, Qi, Ghahramani, Afshin, Raj, Nawin, Yin, Zhenliang and Yang, Linshan. 2021. "Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity." Journal of Hydrology. 599, pp. 1-23. https://doi.org/10.1016/j.jhydrol.2021.126350
An EEMD-BiLSTM algorithm integrated with Boruta random forest optimiser for significant wave height forecasting along coastal areas of Queensland, Australia
Raj, Nawin and Brown, Jason. 2021. "An EEMD-BiLSTM algorithm integrated with Boruta random forest optimiser for significant wave height forecasting along coastal areas of Queensland, Australia." Remote Sensing. 13 (8), pp. 1-20. https://doi.org/10.3390/rs13081456
Design of Alkali-Activated Slag-Fly Ash Concrete Mixtures Using Machine Learning
Gunasekara, C., Lokuge, W., Keskic, M., Raj, N., Law, D. W. and Setunge, S.. 2020. "Design of Alkali-Activated Slag-Fly Ash Concrete Mixtures Using Machine Learning." ACI Materials Journal. 117 (5), pp. 263-278. https://doi.org/10.14359/51727019
Deep Air Quality Forecasts: Suspended Particulate Matter Modeling With Convolutional Neural and Long Short-Term Memory Networks
Sharma, Ekta, Deo, Ravinesh C., Prasad, Ramendra, Parisi, Alfio and Raj, Nawin. 2020. "Deep Air Quality Forecasts: Suspended Particulate Matter Modeling With Convolutional Neural and Long Short-Term Memory Networks." IEEE Access. 8, pp. 209503-209516. https://doi.org/10.1109/ACCESS.2020.3039002
Understanding how climate change threatens food security
Nguyen-Huy, Thong. 2021. "Understanding how climate change threatens food security." A compendium of essays for the Allianz Climate Risk Research Award 2021. Germany.
Drought outlook development
Nguyen-Huy, Thong, Guillory, Laura and Cobon, David. 2021. Drought outlook development. Australia. Northern Australia Climate Program (NACP).
Application of FAIR and CARE Principles in Research Data Management Practice
Gacenga, Francis, Chesters, Racheal, Nguyen-Huy, Thong, Adeyinka, Adewuyi Ayodele and Rose, Samantha. 2021. "Application of FAIR and CARE Principles in Research Data Management Practice." 2021 Australasian Research Management Society VirtualConference (2021 ARMS Virtual Conference Conference): Disrupting the Status Quo: Challenging the Research and Innovation Culture. Online 03 - 05 Nov 2021 Australia.
An evaluation of the effectiveness of adoption and implementation of FAIR (Findable, Accessible, Interoperable and Reusable) data management principles in research – a case study of the University of Southern Queensland
Gacenga, Francis, Chesters, Racheal, Nguyen-Huy, Thong and Rose, Samantha. 2021. "An evaluation of the effectiveness of adoption and implementation of FAIR (Findable, Accessible, Interoperable and Reusable) data management principles in research – a case study of the University of Southern Queensland." 2021 Collaborative Conference on Computational & Data Intensive Science (C3DIS). Online 06 - 08 Jul 2021 Australia.
MARS model for prediction of short- and long-term global solar radiation
Balalla, Dilki T., Nguyen-Huy, Thong and Deo, Ravinesh. 2021. "MARS model for prediction of short- and long-term global solar radiation." Deo, Ravinesh, Roy, Sanjiban Sekhar and Samui, Pijush (ed.) Predictive Modelling for Energy Management and Power Systems Engineering. United Kingdom. Elsevier. pp. 391-436
Development of Flood Monitoring Index for daily flood risk evaluation: case studies in Fiji
Moishin, Mohammed, Deo, Ravinesh C., Prasad, Ramendra, Raj, Nawin and Abdulla, Shahab. 2021. "Development of Flood Monitoring Index for daily flood risk evaluation: case studies in Fiji." Stochastic Environmental Research and Risk Assessment. 35 (7), pp. 1387-1402. https://doi.org/10.1007/s00477-020-01899-6
MARS model for prediction of short- and long-term global solar radiation
Balalla, Dilki T., Nguyen-Huy, Thong and Deo, Ravinesh. 2021. "MARS model for prediction of short- and long-term global solar radiation." Deo, Ravinesh, Samui, Pijush and Roy, Sanjiban Sekhar (ed.) Predictive modelling for energy management and power systems engineering. Amsterdam, Netherlands. Elsevier. pp. 391-436
Daily flood forecasts with intelligent data analytic models: multivariate empirical mode decomposition-based modeling methods
Prasad, Ramendra, Charan, Dhrishna, Joseph, Lionel, Nguyen-Huy, Thong, Deo, Ravinesh C. and Singh, Sanjay. 2021. "Daily flood forecasts with intelligent data analytic models: multivariate empirical mode decomposition-based modeling methods." Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur and Yaseen, Zaher Mundher (ed.) Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation. Singapore. Springer. pp. 359-381
Artificial neural networks for prediction of Steadman Heat Index
Chand, Bhuwan, Nguyen-Huy, Thong and Deo, Ravinesh C.. 2021. "Artificial neural networks for prediction of Steadman Heat Index." Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur and Yaseen, Zaher Mundher (ed.) Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation. Singapore. Springer. pp. 293-357
Bayesian Markov Chain Monte Carlo-based copulas: factoring the role of large-scale climate indices in monthly flood prediction
Nguyen-Huy, Thong, Deo, Ravinesh C., Yaseen, Zaher Mundher, Mushtaq, Shahbaz and Prasad, Ramendra. 2021. "Bayesian Markov Chain Monte Carlo-based copulas: factoring the role of large-scale climate indices in monthly flood prediction." Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur and Yaseen, Zaher Mundher (ed.) Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation. Singapore. Springer. pp. 29-47
Monitoring rice growth status in the Mekong Delta, Vietnam using multitemporal Sentinel-1 data
Phung, Hoang-Phi, Lam-Dao, Nguyen, Nguyen-Huy, Thong, Le-Toan, Thuy and Apan, Armando A.. 2020. "Monitoring rice growth status in the Mekong Delta, Vietnam using multitemporal Sentinel-1 data." Journal of Applied Remote Sensing. 14 (1), pp. 014518-1-014518-23. https://doi.org/10.1117/1.JRS.14.014518
Near real-time global solar radiation forecasting at multiple time-step horizons using the long short-term memory network
Huynh, Anh Ngoc‐Lan, Deo, Ravinesh C., An-Vo, Duc-Anh, Ali, Mumtaz, Raj, Nawin and Abdulla, Shahab. 2020. "Near real-time global solar radiation forecasting at multiple time-step horizons using the long short-term memory network." Energies. 13 (14). https://doi.org/10.3390/en13143517
Not so robust: robusta coffee production is highly sensitive to temperature
Kath, Jarrod, Byrareddy, Vivekananda M., Craparo, Alessandro, Nguyen-Huy, Thong, Mushtaq, Shahbaz, Cao, Loc and Bossolasco, Laurent. 2020. "Not so robust: robusta coffee production is highly sensitive to temperature." Global Change Biology. 26 (6), pp. 3677-3688. https://doi.org/10.1111/gcb.15097
Integrating El Nino-Southern Oscillation information and spatial diversification to minimize risk and maximize profit for Australian grazing enterprises
Nguyen-Huy, Thong, Kath, Jarrod, Mushtaq, Shahbaz, Cobon, David, Stone, Gordon and Stone, Roger. 2020. "Integrating El Nino-Southern Oscillation information and spatial diversification to minimize risk and maximize profit for Australian grazing enterprises." Agronomy for Sustainable Development: sciences des productions vegetales et de l'environnement. 40, pp. 1-11. https://doi.org/10.1007/s13593-020-0605-z
Modern artificial intelligence model development for undergraduate student performance prediction: an investigation on engineering mathematics courses
Deo, Ravinesh C., Yaseen, Zaher Mundher, Al-Ansari, Nadhir, Nguyen-Huy, Thong, Langlands, Trevor and Galligan, Linda. 2020. "Modern artificial intelligence model development for undergraduate student performance prediction: an investigation on engineering mathematics courses." IEEE Access. 8, pp. 136697-136724. https://doi.org/10.1109/ACCESS.2020.3010938
Probabilistic seasonal rainfall forecasts using semiparametric d-vine copula-based quantile regression
Nguyen-Huy, Thong, Deo, Ravinesh C., Mushtaq, Shahbaz and Khan, Shahjahan. 2020. "Probabilistic seasonal rainfall forecasts using semiparametric d-vine copula-based quantile regression." Samui, Pijush, Bui, Dieu Tien, Chakraborty, Subrata and Deo, Ravinesh C. (ed.) Handbook of probabilistic models. Oxford, United Kingdom. Elsevier. pp. 203-227
Wavelet-based 3-phase hybrid SVR model trained with satellite-derived predictors, particle swarm optimization and maximum overlap discrete wavelet transform for solar radiation prediction
Ghimire, Sujan, Deo, Ravinesh C., Raj, Nawin and Mi, Jianchun. 2019. "Wavelet-based 3-phase hybrid SVR model trained with satellite-derived predictors, particle swarm optimization and maximum overlap discrete wavelet transform for solar radiation prediction." Renewable and Sustainable Energy Reviews. 113, pp. 1-19. https://doi.org/10.1016/j.rser.2019.109247
Deep solar radiation forecasting with convolutional neural network and long short-term memory network algorithms
Ghimire, Sujan, Deo, Ravinesh C., Raj, Nawin and Mi, Jianchun. 2019. "Deep solar radiation forecasting with convolutional neural network and long short-term memory network algorithms." Applied Energy. 253, pp. 1-20. https://doi.org/10.1016/j.apenergy.2019.113541
Copula-based statistical modelling of synoptic-scale climate indices for quantifying and managing agricultural risks in australia
Nguyen-Huy, Thong. 2018. Copula-based statistical modelling of synoptic-scale climate indices for quantifying and managing agricultural risks in australia. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/xa1p-8373
Deep Learning Neural Networks Trained with MODIS Satellite-Derived Predictors for Long-Term Global Solar Radiation Prediction
Ghimire, Sujan, Deo, Ravinesh C., Raj, Nawin and Mi, Jianchun. 2019. "Deep Learning Neural Networks Trained with MODIS Satellite-Derived Predictors for Long-Term Global Solar Radiation Prediction." Energies. 12 (12), pp. 1-42. https://doi.org/10.3390/en12122407
Copula statistical models for analyzing stochastic dependencies of systemic drought risk and potential adaptation strategies
Nguyen-Huy, Thong, Deo, Ravinesh C., Mushtaq, Shahbaz, Kath, Jarrod and Khan, Shahjahan. 2019. "Copula statistical models for analyzing stochastic dependencies of systemic drought risk and potential adaptation strategies." Stochastic Environmental Research and Risk Assessment. 33 (3), pp. 779-799. https://doi.org/10.1007/s00477-019-01662-6
Global solar radiation prediction by ANN integrated with European Centre for medium range weather forecast fields in solar rich cities of Queensland Australia
Ghimire, Sujan, Deo, Ravinesh C., Downs, Nathan J. and Raj, Nawin. 2019. "Global solar radiation prediction by ANN integrated with European Centre for medium range weather forecast fields in solar rich cities of Queensland Australia." Journal of Cleaner Production. 216, pp. 288-310. https://doi.org/10.1016/j.jclepro.2019.01.158
Copula-based agricultural conditional value-at-risk modelling for geographical diversifications in wheat farming portfolio management
Nguyen-Huy, Thong, Deo, Ravinesh C., Mushtaq, Shahbaz, Kath, Jarrod and Khan, Shahjahan. 2018. "Copula-based agricultural conditional value-at-risk modelling for geographical diversifications in wheat farming portfolio management." Weather and Climate Extremes. 21, pp. 76-89. https://doi.org/10.1016/j.wace.2018.07.002
Optimization of windspeed prediction using an artificial neural network compared with a genetic programming model
Deo, Ravinesh C., Ghimire, Sujan, Downs, Nathan J. and Raj, Nawin. 2018. "Optimization of windspeed prediction using an artificial neural network compared with a genetic programming model." Kim, Dookie, Roy, Sanjiban Sekhar, Lansivaara, Tim, Deo, Ravinesh C. and Samui, Pijush (ed.) Handbook of research on predictive modeling and optimization methods in science and engineering. Hershey, United States. IGI Global. pp. 328-359
Modeling the joint influence of multiple synoptic-scale, climate mode indices on Australian wheat yield using a vine copula-based approach
Nguyen-Huy, Thong, Deo, Ravinesh C., Mushtaq, Shahbaz, An-Vo, Duc-Anh and Khan, Shahjahan. 2018. "Modeling the joint influence of multiple synoptic-scale, climate mode indices on Australian wheat yield using a vine copula-based approach." European Journal of Agronomy. 98, pp. 65-81. https://doi.org/10.1016/j.eja.2018.05.006
Input selection and data-driven model performance optimization to predict the Standardized Precipitation and Evaporation Index in a drought-prone region
Mouatadid, Soukayna, Raj, Nawin, Deo, Ravinesh C. and Adamowski, Jan F.. 2018. "Input selection and data-driven model performance optimization to predict the Standardized Precipitation and Evaporation Index in a drought-prone region." Atmospheric Research. 212, pp. 130-149. https://doi.org/10.1016/j.atmosres.2018.05.012
Self-adaptive differential evolutionary extreme learning machines for long-term solar radiation prediction with remotely-sensed MODIS satellite and Reanalysis atmospheric products in solar-rich cities
Ghimire, Sujan, Deo, Ravinesh C., Downs, Nathan J. and Raj, Nawin. 2018. "Self-adaptive differential evolutionary extreme learning machines for long-term solar radiation prediction with remotely-sensed MODIS satellite and Reanalysis atmospheric products in solar-rich cities." Remote Sensing of Environment: an interdisciplinary journal. 212, pp. 176-198. https://doi.org/10.1016/j.rse.2018.05.003
Adiabatic decay of internal solitons due to Earth’s rotation within the framework of the Gardner–Ostrovsky equation
Obregon, Maria, Raj, Nawin and Stepanyants, Yury. 2018. "Adiabatic decay of internal solitons due to Earth’s rotation within the framework of the Gardner–Ostrovsky equation." Chaos: an interdisciplinary journal of nonlinear science. 28 (3), pp. 1-11. https://doi.org/10.1063/1.5021864
Copula-statistical precipitation forecasting model in Australia’s agro-ecological zones
Nguyen-Huy, Thong, Deo, Ravinesh C., An-Vo, Duc-Anh, Mushtaq, Shahbaz and Khan, Shahjahan. 2017. "Copula-statistical precipitation forecasting model in Australia’s agro-ecological zones." Agricultural Water Management. 191, pp. 153-172. https://doi.org/10.1016/j.agwat.2017.06.010
Adiabatic decay of internal solitons in a rotating ocean
Obregon, M. A., Raj, N. and Stepanyants, Y. A.. 2016. "Adiabatic decay of internal solitons in a rotating ocean." 20th Australasian Fluid Mechanics Conference (AFMC 2016). Perth, Australia 05 - 08 Dec 2016 Australia.
Nonlinear vector waves of a flexural mode in a chain model of atomic particles
Nikitenkova, S. P., Raj, N. and Stepanyants, Y. A.. 2015. "Nonlinear vector waves of a flexural mode in a chain model of atomic particles." Communications in Nonlinear Science and Numerical Simulation. 20 (3), pp. 731-742. https://doi.org/10.1016/j.cnsns.2014.05.031
Nonlinear spectra of shallow water waves
Giovanangeli, J. -P., Kharif, C., Raj, N. and Stepanyants, Y.. 2013. "Nonlinear spectra of shallow water waves." Oceans - San Diego, 2013. San Diego, United States 23 - 26 Sep 2013 United States. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.23919/OCEANS.2013.6741132
Numerical study of nonlinear wave processes by means of discrete chain models
Obregon, M., Raj, N. and Stepanyants, Y.. 2012. "Numerical study of nonlinear wave processes by means of discrete chain models." Gu, Y. T. and Saha, Suvash C. (ed.) 4th International Conference on Computational Methods (ICCM 2012). Gold Coast, Australia 25 - 28 Nov 2012 Brisbane, Australia.