Evaluating management strategies for sustainable crop production under changing climate conditions: a system dynamics approach
Article
Article Title | Evaluating management strategies for sustainable crop production under changing climate conditions: a system dynamics approach |
---|---|
ERA Journal ID | 5850 |
Article Category | Article |
Authors | Pham, Yen Hoang (Author), Reardon-Smith, Kathryn (Author) and Deo, Ravinesh C. (Author) |
Journal Title | Journal of Environmental Management |
Journal Citation | 292 |
Article Number | 112790 |
Number of Pages | 12 |
Year | 2021 |
Publisher | Elsevier |
Place of Publication | United Kingdom |
ISSN | 0301-4797 |
1093-0191 | |
1095-8630 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.jenvman.2021.112790 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S0301479721008525 |
Abstract | The increasing frequency and severity of drought pose significant threats to sustainable agricultural production across the world. Managing drought risks is challenging given the complexity of the interdependencies and feedback between climate drivers and socio-economic and ecological systems. To better understand the dynamics that drive the impacts of drought and water scarcity on crop production, a system dynamics model has been developed to explore complex interactions between factors in associated with drought and agricultural production, and examine how these might impact agricultural sustainability, using a case study in a coffee production system in Viet Nam. The model shows that water- and land-use drivers and their interactions with ecological and socio-economic factors play a more significant role than drought in determining the sustainability of coffee production. Results of policy scenario analyses indicate that drought conditions might exacerbate problems related to water shortages for irrigation but their impacts could be substantially minimized through applying intervention strategies, including restriction of the total area of land available for coffee production (to ~ 190,000 ha) and a 25% reduction in the irrigation amount per hectare of coffee compared to the common practices. Overall, the model findings add significant insight into drought and water resources management for sustainable crop production and the developed model can serve as a decision-support tool to inform strategic policy-making. |
Keywords | agricultural production; water management; land use; drought; water scarcity; systems thinking |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 410406. Natural resource management |
300207. Agricultural systems analysis and modelling | |
300205. Agricultural production systems simulation | |
410404. Environmental management | |
410199. Climate change impacts and adaptation not elsewhere classified | |
300203. Agricultural land planning | |
300202. Agricultural land management | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Faculty of Health, Engineering and Sciences |
Centre for Applied Climate Sciences | |
School of Sciences | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q65v5/evaluating-management-strategies-for-sustainable-crop-production-under-changing-climate-conditions-a-system-dynamics-approach
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Ghimire, Sujan, Bhandari, Binayak, Casillas-Perez, David, Deo, Ravinesh C. and Salcedo-sanz, Sancho. 2022. "Hybrid deep CNN-SVR algorithm for solar radiation prediction problems in Queensland, Australia." Engineering Applications of Artificial Intelligence. 112, pp. 1-26. https://doi.org/10.1016/j.engappai.2022.104860Boosting solar radiation predictions with global climate models, observational predictors and hybrid deep-machine learning algorithms
Ghimire, Sujan, Deo, Ravinesh C., Casillas-Perez, David and Salcedo-sanz, Sancho. 2022. "Boosting solar radiation predictions with global climate models, observational predictors and hybrid deep-machine learning algorithms." Applied Energy. 316, pp. 1-25. https://doi.org/10.1016/j.apenergy.2022.119063Machine learning regression and classification methods for fog events prediction
Castillo-Boton, C., Casillas-Perez, D., Casanova-Mateo, C., Ghimire, S., Cerro-Prada, E., Gutierrez, P. A., Deo, R. C. and Salcedo-sanz, S.. 2022. "Machine learning regression and classification methods for fog events prediction." Atmospheric Research. 272, pp. 1-23. https://doi.org/10.1016/j.atmosres.2022.106157Efficient water management and irrigation on farms
Reardon-Smith, K., Mushtaq, Shahbaz, Scobie, M., Eberhard, J. and Maraseni, T. N.. 2022. "Efficient water management and irrigation on farms." Sims, Ralph E. H. (ed.) Energy-smart farming: efficiency, renewable energy and sustainability. United Kingdom. Burleigh Dodds Science Publishing Limited. pp. 102-134Quantum Artificial Intelligence Predictions Enhancement by Improving Signal Processing
Riaz, Farina, Abdulla, Shahab, Ni, Wei, Radfar, Mohsen, Deo, Ravinesh and Hopkins, Susan. 2022. "Quantum Artificial Intelligence Predictions Enhancement by Improving Signal Processing." Quantum Australia Conference 2022. Online 23 - 25 Feb 2022 Toowoomba, Australia. https://doi.org/10.13140/RG.2.2.34754.66245Deep learning CNN-LSTM-MLP hybrid fusion model for feature optimizations and daily solar radiation prediction
Ghimire, Sujan, Deo, Ravinesh C., Casillas-Perez, David, Salcedo-sanz, Sancho, Sharma, Ekta and Ali, Mumtaz. 2022. "Deep learning CNN-LSTM-MLP hybrid fusion model for feature optimizations and daily solar radiation prediction." Measurement. 202, pp. 1-22. https://doi.org/10.1016/j.measurement.2022.111759Basin management inspiration from impacts of alternating dry and wet conditions on water production and carbon uptake in Murray-Darling Basin
Lu, Zhixiang, Feng, Qi, Wei, Yongping, Zhao, Yan, Deo, Ravinesh C., Xie, Jiali, Zhou, Sha, Zhu, Meng and Xu, Min. 2022. "Basin management inspiration from impacts of alternating dry and wet conditions on water production and carbon uptake in Murray-Darling Basin." Science of the Total Environment. 851 (Part 2), pp. 1-8. https://doi.org/10.1016/j.scitotenv.2022.158359Introductory Engineering Mathematics Students’ Weighted Score Predictions Utilising a Novel Multivariate Adaptive Regression Spline Model
Ahmed, Abul Abrar Masrur, Deo, Ravinesh C., Ghimire, Sujan, Downs, Nathan J., Devi, Aruna, Barua, Prabal D. and Yaseen, Zaher M.. 2022. "Introductory Engineering Mathematics Students’ Weighted Score Predictions Utilising a Novel Multivariate Adaptive Regression Spline Model." Sustainability. 14 (17), pp. 1-27. https://doi.org/10.3390/su141711070Kernel Ridge Regression Hybrid Method for Wheat Yield Prediction with Satellite-Derived Predictors
Ahmed, A. A. Masrur, Sharma, Ekta, Jui, S. Janifer Jabin, Deo, Ravinesh C., Nguyen-Huy, Thong and Ali, Mumtaz. 2022. "Kernel Ridge Regression Hybrid Method for Wheat Yield Prediction with Satellite-Derived Predictors." Remote Sensing. 14 (5), pp. 1-24. https://doi.org/10.3390/rs14051136Cloud Affected Solar UV Predictions with Three-Phase Wavelet Hybrid Convolutional Long Short-Term Memory Network Multi-Step Forecast System
Prasad, Salvin S., Deo, Ravinesh C., Downs, Nathan, Igoe, Damien, Parisi, Alfio V. and Soar, Jeffrey. 2022. "Cloud Affected Solar UV Predictions with Three-Phase Wavelet Hybrid Convolutional Long Short-Term Memory Network Multi-Step Forecast System." IEEE Access. 10, pp. 24704-24720. https://doi.org/10.1109/ACCESS.2022.3153475Development and evaluation of hybrid deep learning long short-term memory network model for pan evaporation estimation trained with satellite and ground-based data
Jayasinghe, W. J. M. Lakmini Prarthana, Deo, Ravinesh C., Ghahramani, Afshin, Ghimire, Sujan and Raj, Nawin. 2022. "Development and evaluation of hybrid deep learning long short-term memory network model for pan evaporation estimation trained with satellite and ground-based data." Journal of Hydrology. 607, pp. 1-19. https://doi.org/10.1016/j.jhydrol.2022.127534Integrative artificial intelligence models for Australian coastal sediment lead prediction: An investigation of in-situ measurements and meteorological parameters effects
Bhagat, Suraj Kumar, Tiyasha, Tiyasha, Kumar, Adarsh, Malik, Tabarak, Jawad, Ali H., Khedher, Khaled Mohamed, Deo, Ravinesh C. and Yaseen, Zaher Mundher. 2022. "Integrative artificial intelligence models for Australian coastal sediment lead prediction: An investigation of in-situ measurements and meteorological parameters effects." Journal of Environmental Management. 309, pp. 1-16. https://doi.org/10.1016/j.jenvman.2022.114711An Eigenvalues-Based Covariance Matrix Bootstrap Model Integrated With Support Vector Machines for Multichannel EEG Signals Analysis
Al-Hadeethi, Hanan, Abdulla, Shahab, Diykh, Mohammed, Deo, Ravinesh C. and Green, Jonathan H.. 2022. "An Eigenvalues-Based Covariance Matrix Bootstrap Model Integrated With Support Vector Machines for Multichannel EEG Signals Analysis." Frontiers in Neuroinformatics. 15, pp. 1-15. https://doi.org/10.3389/fninf.2021.808339Stacked LSTM Sequence-to-Sequence Autoencoder with Feature Selection for Daily Solar Radiation Prediction: A Review and New Modeling Results
Ghimire, Sujan, Deo, Ravinesh C., Wang, Hua, Al-Musaylh, Mohanad S., Casillas-Perez, David and Salcedo-sanz, Sancho. 2022. "Stacked LSTM Sequence-to-Sequence Autoencoder with Feature Selection for Daily Solar Radiation Prediction: A Review and New Modeling Results." Energies. 15 (3), pp. 1-39. https://doi.org/10.3390/en15031061Texture analysis based graph approach for automatic detection of neonatal seizure from multi-channel EEG signals
Diykh, Mohammed, Miften, Firas Sabar, Abdulla, Shahab, Deo, Ravinesh C., Siuly, Siuly, Green, Jonathan H. and Oudah, Atheer Y.. 2022. "Texture analysis based graph approach for automatic detection of neonatal seizure from multi-channel EEG signals." Measurement. 190 (110731), pp. 1-13. https://doi.org/10.1016/j.measurement.2022.110731Classification of catchments for nitrogen using Artificial Neural Network Pattern Recognition and spatial data
O'Sullivan, Cherie M., Ghahramani, Afshin, Deo, Ravinesh C., Pembleton, Keith, Khan, Urooj and Tuteja, Narendra. 2022. "Classification of catchments for nitrogen using Artificial Neural Network Pattern Recognition and spatial data." Science of the Total Environment. 809, pp. 1-15. https://doi.org/10.1016/j.scitotenv.2021.151139Drought Outlook Products Review
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An-Vo, Duc-Anh, Radanielson, Ando Mariot, Mushtaq, Shahbaz, Reardon-Smith, Kate and Hewitt, Chris. 2021. "A framework for assessing the value of seasonal climate forecasting in key agricultural decisions." Climate Services. 22, pp. 1-14. https://doi.org/10.1016/j.cliser.2021.100234Domino effect of climate change over two millennia in ancient China’s Hexi Corridor
Feng, Qi, Yan, Linshan, Deo, Ravinesh C., AghaKouchak, Amir, Adamowski, Jan F., Stone, Roger, Yin, Zhenliang, Liu, Wei, Si, Jianhua, Wen, Xiaohu, Zhu, Meng and Cao, Shixiong. 2019. "Domino effect of climate change over two millennia in ancient China’s Hexi Corridor." Nature Sustainability. 2, pp. 957-961. https://doi.org/10.1038/s41893-019-0397-9Bat algorithm for dam–reservoir operation
Ethteram, Mohammad, Mousavi, Sayed-Farhad, Karami, Hojat, Farzin, Saeed, Deo, Ravinesh, Othman, Faridah Binti, Chau, Kwok-Wing, Sarkamaryan, Saeed, Singh, Vijay P. and El-Shafie, Ahmed. 2018. "Bat algorithm for dam–reservoir operation." Environmental Earth Sciences. 77 (13), pp. 1-15. https://doi.org/10.1007/s12665-018-7662-5Characteristics of ecosystem water use efficiency in a desert riparian forest
Ma, Xiaohong, Feng, Qi, Su, Yonghong, Yu, Tengfei and Deo, Ravinesh C.. 2018. "Characteristics of ecosystem water use efficiency in a desert riparian forest." Environmental Earth Sciences. 77 (358). https://doi.org/10.1007/s12665-018-7518-zThe influence of climatic inputs on stream-flow pattern forecasting: case study of Upper Senegal River
Diop, Lamine, Bodian, Ansoumana, Djaman, Koffi, Yaseen, Zaher Mundher, Deo, Ravinesh C., El-Shafie, Ahmed and Brown, Larry C.. 2018. "The influence of climatic inputs on stream-flow pattern forecasting: case study of Upper Senegal River." Environmental Earth Sciences. 77 (5). https://doi.org/10.1007/s1266Uncertainty assessment of the multilayer perceptron (MLP) neural network model with implementation of the novel hybrid MLP-FFA method for prediction of biochemical oxygen demand and dissolved oxygen: a case study of Langat River
Raheli, Bahare, Aalami, Mohammad Taghi, El-Shafie, Ahmed, Ghorbani, Mohammad Ali and Deo, Ravinesh C.. 2017. "Uncertainty assessment of the multilayer perceptron (MLP) neural network model with implementation of the novel hybrid MLP-FFA method for prediction of biochemical oxygen demand and dissolved oxygen: a case study of Langat River." Environmental Earth Sciences. 76 (14). https://doi.org/10.1007/s12665-017-6842-z![](/~234/dnn/default-thumbnail.png)