Feedback modelling of the impacts of drought: A case study in coffee production systems in Viet Nam
Article
Pham, Yen, Reardon-Smith, Kathryn, Mushtaq, Shahbaz and Deo, Ravinesh C.. 2020. "Feedback modelling of the impacts of drought: A case study in coffee production systems in Viet Nam." Climate Risk Management. 30, pp. 1-17. https://doi.org/10.1016/j.crm.2020.100255
| Article Title | Feedback modelling of the impacts of drought: A case study in coffee production systems in Viet Nam |
|---|---|
| ERA Journal ID | 200297 |
| Article Category | Article |
| Authors | Pham, Yen (Author), Reardon-Smith, Kathryn (Author), Mushtaq, Shahbaz (Author) and Deo, Ravinesh C. (Author) |
| Journal Title | Climate Risk Management |
| Journal Citation | 30, pp. 1-17 |
| Article Number | 100255 |
| Number of Pages | 17 |
| Year | 2020 |
| Publisher | Elsevier |
| Place of Publication | Netherlands |
| ISSN | 2212-0963 |
| Digital Object Identifier (DOI) | https://doi.org/10.1016/j.crm.2020.100255 |
| Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S2212096320300450 |
| Abstract | Drought is a major cause of crop failure and livelihood insecurity, affecting millions of people across the world. A changing climate, increasing population and economic growth are exacerbating water shortages, further interrupting agricultural production. Assessing and minimizing the impacts of drought require a thorough understanding of the interrelationships and interactions between the climate system, ecosystems and human systems. In this paper, we apply causal loop modelling grounded in systems thinking theory to examine the interdependencies and feedback processes among factors associated with drought that impact crop production using a case study of Robusta coffee production systems in Viet Nam – the world’s second-largest coffee producing country. Our model, underpinned by qualitative data from consultation with a range of stakeholders, indicates that water depletion affecting coffee cultivation is not solely attributed to rainfall insufficiency but an outcome of complex interactions between climate and socio-economic systems. Our analysis highlights that uncontrollable coffee expansion, largely at the expense of forested areas, is partly the unintended consequence of policy decisions, including those encouraging migration and perennial crop development. Growing water demand in the region, including the demand for irrigation water driven by the ever-increasing area under coffee cultivation, as well as inefficient irrigation practices are placing significant pressure on water resources. A changing climate may exacerbate the problem, further impacting coffee cultivation, unless adaptation practices occur. A number of potential interventions are suggested, including explicit zoning of coffee-growing areas; awareness raising for wide adoption of optimal irrigation practices; converting Robusta coffee monocultures to diversified systems; and strictly protecting existing forests coupled with afforestation and reforestation. These interventions should be simultaneously implemented in order to adequately address drought and water scarcity for coffee production and build resilience to climate and market risks. |
| Keywords | System dynamics; Causal loop diagram; Conceptual modelling; Feedback loops; Mental models; Stakeholder engagement |
| Contains Sensitive Content | Does not contain sensitive content |
| ANZSRC Field of Research 2020 | 300207. Agricultural systems analysis and modelling |
| 410404. Environmental management | |
| 300402. Agro-ecosystem function and prediction | |
| Byline Affiliations | Faculty of Health, Engineering and Sciences |
| Centre for Applied Climate Sciences | |
| School of Sciences | |
| Institution of Origin | University of Southern Queensland |
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Xu, Shuting, Deo, Ravinesh C, Soar, Jeffrey, Barua, Prabal Datta, Faust, Oliver, Homaira, Nusrat, Jaffe, Adam, Kabir, Arm Luthful and Acharya, U. Rajendra. 2023. "Automated detection of airflow obstructive diseases: A systematic review of the last decade (2013-2022)." Computer Methods and Programs in Biomedicine. 241. https://doi.org/10.1016/j.cmpb.2023.107746Brain tumor detection and screening using artificial intelligence techniques: Current trends and future perspectives
Raghavendra, U., Gudigar, Anjan, Paul, Aritra, Goutham, T.S., Inamdar, Mahesh Anil, Hegde, Ajay, Dev, Aruna, Ooi, Chui Ping, Deo, Ravinesh C., Barua, Prabal Datta, Molinari, Filippo, Ciaccio, Edward J. and Acharya, U. Rajendra. 2023. "Brain tumor detection and screening using artificial intelligence techniques: Current trends and future perspectives." Computers in Biology and Medicine. 163. https://doi.org/10.1016/j.compbiomed.2023.107063Application of Entropy for Automated Detection of Neurological Disorders With Electroencephalogram Signals: A Review of the Last Decade (2012-2022)
Jui, S. Janifer Jabin, Deo, Ravinesh C. Deo, Barua, Prabal Datta, Devi, Aruna, Soar, Jeffrey and Acharya, U. Rajendra. 2023. "Application of Entropy for Automated Detection of Neurological Disorders With Electroencephalogram Signals: A Review of the Last Decade (2012-2022)." IEEE Access. 11, pp. 71905-71924. https://doi.org/10.1109/ACCESS.2023.3294473Integrated Multi-Head Self-Attention Transformer model for electricity demand prediction incorporating local climate variables
Ghimire, Sujan, Nguyen-Huy, Thong, AL-Musaylh, Mohanad S., Deo, Ravinesh C., Casillas-Perez, David and Salcedo-sanz, Sancho. 2023. "Integrated Multi-Head Self-Attention Transformer model for electricity demand prediction incorporating local climate variables." Energy and AI. 14. https://doi.org/10.1016/j.egyai.2023.100302The Great 2011 Thailand flood disaster revisited: Could it have been mitigated by different dam operations based on better weather forecasts?
Loc, Ho Huu, Emadzadeh, Adel, Park, Edward, Nontikansak, Piyanuch and Deo, Ravinesh C.. 2023. "The Great 2011 Thailand flood disaster revisited: Could it have been mitigated by different dam operations based on better weather forecasts? " Environmental Research. 216 (Part 2). https://doi.org/10.1016/j.envres.2022.114493Comparison of machine learning methods emulating process driven crop models
Johnston, David B., Pembleton, Keith G., Huth, Neil I. and Deo, Ravinesh C.. 2023. "Comparison of machine learning methods emulating process driven crop models ." Environmental Modelling and Software. 162. https://doi.org/10.1016/j.envsoft.2023.105634A novel approach based on integration of convolutional neural networks and echo state network for daily electricity demand prediction
Ghimire, Sujan, Nguyen-Huy, Thong, AL-Musaylh, Mohanad S., Deo, Ravinesh, Casillas-Perez, David and Salcedo-sanz, Sancho. 2023. "A novel approach based on integration of convolutional neural networks and echo state network for daily electricity demand prediction." Energy. 275, p. 127430. https://doi.org/10.1016/j.energy.2023.127430Accurate Image Multi-Class Classification Neural Network Model with Quantum Entanglement Approach
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Joseph, Lionel P., Deo, Ravinesh C., Prasad, Ramendra, Salcedo-Sanz, Sancho, Raj, Nawin and Soar, Jeffrey. 2023. "Near real-time wind speed forecast model with bidirectional LSTM networks." Renewable Energy. 204, pp. 39-58. https://doi.org/10.1016/j.renene.2022.12.123Downscaling Surface Albedo to Higher Spatial Resolutions With an Image Super-Resolution Approach and PROBA-V Satellite Images
Deo, Ravinesh C., Karalasingham, Sagthitharan, Casillas-Perez, David, Raj, Narwin and Salcedo-sanz, Sancho. 2023. "Downscaling Surface Albedo to Higher Spatial Resolutions With an Image Super-Resolution Approach and PROBA-V Satellite Images." IEEE Access. 11, pp. 5558-5577. https://doi.org/10.1109/ACCESS.2023.3236253Developing a novel hybrid method based on dispersion entropy and adaptive boosting algorithm for human activity recognition
Diykh, Mohammed, Abdulla, Shahab, Deo, Ravinesh C, Siuly, Siuly and Ali, Mumtaz. 2023. "Developing a novel hybrid method based on dispersion entropy and adaptive boosting algorithm for human activity recognition." Computer Methods and Programs in Biomedicine. 229. https://doi.org/10.1016/j.cmpb.2022.107305Cloud cover bias correction in numerical weather models for solar energy monitoring and forecasting systems with kernel ridge regression
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Nguyen-Huy, Thong, Deo, Ravinesh C., Khan, Shahjahan, Devi, Aruna, Adeyinka, Adewuyi Ayodele, Apan, Armando A. and Yaseen, Zaher Mundher. 2022. "Student Performance Predictions for Advanced Engineering Mathematics Course With New Multivariate Copula Models." IEEE Access. 10, pp. 45112 -45136. https://doi.org/10.1109/ACCESS.2022.3168322Groundwater-surface water interactions at wetland interface: Advancement in catchment system modeling
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Ahmadianfar, Iman, Noori, Ramzia Majeed, Togun, Hussein, Falah, Mayadah W., Homod, Raad Z., Fu, Minglei, Halder, Bijay, Deo, Ravinesh and Yaseen, Zaher Mundher. 2022. "Multi-strategy Slime Mould Algorithm for hydropower multi-reservoir systems optimization." Knowledge-Based Systems. 250, pp. 1-18. https://doi.org/10.1016/j.knosys.2022.109048Suspended sediment load modeling using advanced hybrid rotation forest based elastic network approach
Khosravi, Khabat, Golkarian, Ali, Melesse, Assefa M. and Deo, Ravinesh C.. 2022. "Suspended sediment load modeling using advanced hybrid rotation forest based elastic network approach." Journal of Hydrology. 610, pp. 1-14. https://doi.org/10.1016/j.jhydrol.2022.127963Delineating the Crop-Land Dynamic due to Extreme Environment Using Landsat Datasets: A Case Study
Halder, Bijay, Bandyopadhyay, Jatisankar, Afan, Haitham Abdulmohsin, Naser, Maryam H., Abed, Salwan Ali, Khedher, Khaled Mohamed, Falih, Khaldoon T., Deo, Ravinesh, Scholz, Miklas and Yaseen, Zaher Mundher. 2022. "Delineating the Crop-Land Dynamic due to Extreme Environment Using Landsat Datasets: A Case Study." Agronomy. 12 (6), pp. 1-23. https://doi.org/10.3390/agronomy12061268Coupled online sequential extreme learning machine model with ant colony optimization algorithm for wheat yield prediction
Ali, Mumtaz, Deo, Ravinesh C., Xiang, Yong, Prasad, Ramendra, Li, Jianxin, Farooque, Aitazaz and Yaseen, Zaher Mundher. 2022. "Coupled online sequential extreme learning machine model with ant colony optimization algorithm for wheat yield prediction." Scientific Reports. 12 (1), pp. 1-23. https://doi.org/10.1038/s41598-022-09482-5Forecasting solar photosynthetic photon flux density under cloud cover effects: novel predictive model using convolutional neural network integrated with long short-term memory network
Deo, Ravinesh C., Grant, Richard H., Webb, Ann, Ghimire, Sujan, Igoe, Damien P., Downs, Nathan J., Al-Musaylh, Mohanad S., Parisi, Alfio V. and Soar, Jeffrey. 2022. "Forecasting solar photosynthetic photon flux density under cloud cover effects: novel predictive model using convolutional neural network integrated with long short-term memory network." Stochastic Environmental Research and Risk Assessment. 36, p. 3183–3220. https://doi.org/10.1007/s00477-022-02188-0Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise Deep Residual model for short-term multi-step solar radiation prediction
Ghimire, Sujan, Deo, Ravinesh C, Casillas-Perez, David and Salcedo-sanz, Sancho. 2022. "Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise Deep Residual model for short-term multi-step solar radiation prediction." Renewable Energy. 190, pp. 408-424. https://doi.org/10.1016/j.renene.2022.03.120Efficient daily solar radiation prediction with deep learning 4-phase convolutional neural network, dual stage stacked regression and support vector machine CNN-REGST hybrid model
Ghimire, Sujan, Nguyen-Huy, Thong, Deo, Ravinesh C., Casillas-Perez, David and Salcedo-sanz, Sancho. 2022. "Efficient daily solar radiation prediction with deep learning 4-phase convolutional neural network, dual stage stacked regression and support vector machine CNN-REGST hybrid model." Sustainable Materials and Technologies. 32, pp. 1-24. https://doi.org/10.1016/j.susmat.2022.e00429Hybrid deep CNN-SVR algorithm for solar radiation prediction problems in Queensland, Australia
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
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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.2.2.34754.66245A satellite-based Standardized Antecedent Precipitation Index (SAPI) for mapping extreme rainfall risk in Myanmar
Nguyen-Huy, Thong, Kath, Jarrod, Nagler, Thomas, Khaung, Ye, Aung, Thee Su Su, Mushtaq, Shahbaz, Marcussen, Torben and Stone, Roger. 2022. "A satellite-based Standardized Antecedent Precipitation Index (SAPI) for mapping extreme rainfall risk in Myanmar." Remote Sensing Applications: Society and Environment. 26, pp. 1-19. https://doi.org/10.1016/j.rsase.2022.100733Nuanced assessment of livelihood resilience through the intersectional lens of gender and ethnicity: evidence from small-scale farming communities in the upland regions of Vietnam
Tran, Van Thanh, An-Vo, Duc-Anh, Mushtaq, Shahbaz and Cockfield, Geoff. 2022. "Nuanced assessment of livelihood resilience through the intersectional lens of gender and ethnicity: evidence from small-scale farming communities in the upland regions of Vietnam." Journal of Rural Studies. 92, pp. 68-78. https://doi.org/10.1016/j.jrurstud.2022.03.011Deep learning CNN-LSTM-MLP hybrid fusion model for feature optimizations and daily solar radiation prediction
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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
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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
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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.2022.110731An improved calibration technique to address high dimensionality and non-linearity in integrated groundwater and surface water models
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