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Duc-Anh An-Vo
Centre for Applied Climate Sciences, University of Southern Queensland, Toowoomba 4350, Australia

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Journal article
Published: 24 June 2021 in Sustainability
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Climate variability, climate change, and extreme events can compound the vulnerability of people heavily reliant on agriculture. Those with intersecting disadvantages, such as women, the poor, and ethnic minority groups, may be particularly affected. Understanding and assessing diverse vulnerabilities, especially those related to ethnicity, are therefore potentially important to the development of policies and programs aimed at enabling adaptation in such groups. This study uses a livelihood vulnerability index (LVI) method, along with qualitative data analysis, to compare the vulnerability of different smallholder farmers in Son La province, one of the poorest provinces in Vietnam. Data were collected from 240 households, representing four minority ethnic groups. The results indicated that household vulnerability is influenced by factors such as income diversity, debt, organizational membership, support from and awareness by local authorities, access to health services, water resources, and location. Results revealed that two of the ethnic groups’ households were, on average, more vulnerable, particularly regarding livelihood strategies, health, water, housing and productive land, and social network items when compared to the other two ethnic groups. The study shows the need for targeted interventions to reduce the vulnerability of these and similarly placed small ethnic communities.

ACS Style

Van Tran; Duc-Anh An-Vo; Geoff Cockfield; Shahbaz Mushtaq. Assessing Livelihood Vulnerability of Minority Ethnic Groups to Climate Change: A Case Study from the Northwest Mountainous Regions of Vietnam. Sustainability 2021, 13, 7106 .

AMA Style

Van Tran, Duc-Anh An-Vo, Geoff Cockfield, Shahbaz Mushtaq. Assessing Livelihood Vulnerability of Minority Ethnic Groups to Climate Change: A Case Study from the Northwest Mountainous Regions of Vietnam. Sustainability. 2021; 13 (13):7106.

Chicago/Turabian Style

Van Tran; Duc-Anh An-Vo; Geoff Cockfield; Shahbaz Mushtaq. 2021. "Assessing Livelihood Vulnerability of Minority Ethnic Groups to Climate Change: A Case Study from the Northwest Mountainous Regions of Vietnam." Sustainability 13, no. 13: 7106.

Journal article
Published: 01 April 2021 in Climate Services
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While climate information services are widely available, translating climate information into actionable solutions to reduce climate risk, which are readily taken up by producers, remains a critical challenge. Here, we apply a bio-economic approach to assess the potential economic value of seasonal climate forecasts (SCFs) as a basis for climate services for use in agricultural decision-making. We use a case study approach, quantifying the impacts of seasonal precipitation on rice cropping, a dominant farming system in the Greater Mekong Region (GMR) in Southeast Asia. We demonstrate values of seasonal precipitation forecasts for a range of forecast skill levels from low to perfect skill for three seasonal precipitation conditions (wet, normal and dry), as well as extreme conditions (extreme wet and extreme dry). Based on our integrated bio-economic assessment and seasonal variation in precipitation, we identify an optimal rice sowing window, which potentially results in improved yield and economic benefits compared with the currently applied sowing window. Applying this approach using common rice varieties grown by farmers – specifically, the medium growth duration Jasmine rice and the short duration Vietnamese long grain white rice variety OM 5451 – we find significant value in using seasonal precipitation forecasts to identify optimal sowing windows, ranging from an average of $135 ha−1 for precipitation forecasts at the current level (70% accuracy) of forecast skill to $220 ha−1 for perfect (100% accurate) precipitation forecasts. We propose that such a framework can be used to examine the value of using seasonal climate forecasts, even at current skill levels, in farm adaptive operational decision-making. We envisage that demonstration of the value of using seasonal forecasts in crop production system decisions will build user confidence and help in upscaling the use of climate information in the region and more broadly.

ACS Style

Duc-Anh An-Vo; Ando Mariot Radanielson; Shahbaz Mushtaq; Kate Reardon-Smith; Chris Hewitt. A framework for assessing the value of seasonal climate forecasting in key agricultural decisions. Climate Services 2021, 22, 100234 .

AMA Style

Duc-Anh An-Vo, Ando Mariot Radanielson, Shahbaz Mushtaq, Kate Reardon-Smith, Chris Hewitt. A framework for assessing the value of seasonal climate forecasting in key agricultural decisions. Climate Services. 2021; 22 ():100234.

Chicago/Turabian Style

Duc-Anh An-Vo; Ando Mariot Radanielson; Shahbaz Mushtaq; Kate Reardon-Smith; Chris Hewitt. 2021. "A framework for assessing the value of seasonal climate forecasting in key agricultural decisions." Climate Services 22, no. : 100234.

Journal article
Published: 07 October 2020 in Journal of Cleaner Production
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Climate change is a multifaceted problem impacting social, economic and environmental values. Strategies to reduce climate change impacts require novel and integrated solutions that simultaneously benefit multiple parts of society and minimise potential conflict between economic, food production and environmental values. Here, we use a novel integrated analysis of the energy-water-food nexus, land use, and climate change to explore whether mounting environmental pressure can be reversed without negative consequences on food production and economic outcomes. Using Australia as a test case, our results show the significant potential of optimal use of land and water resources in achieving both increased crop production and reduced greenhouse gas (GHG) emissions while sustaining economic outcomes. Our trade-off analysis shows that, at a regional level, up to 50% reduction in GHG emissions from irrigated crop production is possible without compromising total gross margins; in addition, regional optimisation of resource use resulted in surplus water and land available for environmental planting. Our analysis also indicates that further emissions reduction without trade-offs can be achieved with a higher carbon price and/or where water markets ensure higher value water use. To our knowledge, this is the first future-looking modelling to integrate this range of crop production, environmental and economic issues. This type of integrated approach has potential to better inform government emission reduction policy aimed at finding an equitable and sustainable balance across multiple policy areas.

ACS Style

Tek Maraseni; Duc-Anh An-Vo; Shahbaz Mushtaq; Kate Reardon-Smith. Carbon smart agriculture: An integrated regional approach offers significant potential to increase profit and resource use efficiency, and reduce emissions. Journal of Cleaner Production 2020, 282, 124555 .

AMA Style

Tek Maraseni, Duc-Anh An-Vo, Shahbaz Mushtaq, Kate Reardon-Smith. Carbon smart agriculture: An integrated regional approach offers significant potential to increase profit and resource use efficiency, and reduce emissions. Journal of Cleaner Production. 2020; 282 ():124555.

Chicago/Turabian Style

Tek Maraseni; Duc-Anh An-Vo; Shahbaz Mushtaq; Kate Reardon-Smith. 2020. "Carbon smart agriculture: An integrated regional approach offers significant potential to increase profit and resource use efficiency, and reduce emissions." Journal of Cleaner Production 282, no. : 124555.

Journal article
Published: 02 August 2020 in Water
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Study region: North Johnstone catchment, located in the north east of Australia. The catchment has wet tropical climate conditions and is one of the major sediment contributors to the Great Barrier Reef. Study focus: The purpose of this paper was to identify soil erosion hotspots through simulating hydrological processes, soil erosion and sediment transport using the Soil and Water Assessment Tool (SWAT). In particular, we focused on predictive uncertainty in the model evaluations and presentations—a major knowledge gap for hydrology and soil erosion modelling in the context of Great Barrier Reef catchments. We carried out calibration and validation along with uncertainty analysis for streamflow and sediment at catchment and sub-catchment scales and investigated details of water balance components, the impact of slope steepness and spatio-temporal variations on soil erosion. The model performance in simulating actual evapotranspiration was compared with those of the Australian Landscape Water Balance (AWRA-L) model to increase our confidence in simulating water balance components. New hydrological insights for the region: The spatial locations of soil erosion hotspots were identified and their responses to different climatic conditions were quantified. Furthermore, a set of land use scenarios were designed to evaluate the effect of reforestation on sediment transport. We anticipate that protecting high steep slopes areas, which cover a relatively small proportion of the catchment (4–9%), can annually reduce 15–26% sediment loads to the Great Barrier Reef.

ACS Style

Vahid Rafiei; Afshin Ghahramani; Duc-Anh An-Vo; Shahbaz Mushtaq. Modelling Hydrological Processes and Identifying Soil Erosion Sources in a Tropical Catchment of the Great Barrier Reef Using SWAT. Water 2020, 12, 2179 .

AMA Style

Vahid Rafiei, Afshin Ghahramani, Duc-Anh An-Vo, Shahbaz Mushtaq. Modelling Hydrological Processes and Identifying Soil Erosion Sources in a Tropical Catchment of the Great Barrier Reef Using SWAT. Water. 2020; 12 (8):2179.

Chicago/Turabian Style

Vahid Rafiei; Afshin Ghahramani; Duc-Anh An-Vo; Shahbaz Mushtaq. 2020. "Modelling Hydrological Processes and Identifying Soil Erosion Sources in a Tropical Catchment of the Great Barrier Reef Using SWAT." Water 12, no. 8: 2179.

Journal article
Published: 08 July 2020 in Energies
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This paper aims to develop the long short-term memory (LSTM) network modelling strategy based on deep learning principles, tailored for the very short-term, near-real-time global solar radiation (GSR) forecasting. To build the prescribed LSTM model, the partial autocorrelation function is applied to the high resolution, 1 min scaled solar radiation dataset that generates statistically significant lagged predictor variables describing the antecedent behaviour of GSR. The LSTM algorithm is adopted to capture the short- and the long-term dependencies within the GSR data series patterns to accurately predict the future GSR at 1, 5, 10, 15, and 30 min forecasting horizons. This objective model is benchmarked at a solar energy resource rich study site (Bac-Ninh, Vietnam) against the competing counterpart methods employing other deep learning, a statistical model, a single hidden layer and a machine learning-based model. The LSTM model generates satisfactory predictions at multiple-time step horizons, achieving a correlation coefficient exceeding 0.90, outperforming all of the counterparts. In accordance with robust statistical metrics and visual analysis of all tested data, the study ascertains the practicality of the proposed LSTM approach to generate reliable GSR forecasts. The Diebold–Mariano statistic test also shows LSTM outperforms the counterparts in most cases. The study confirms the practical utility of LSTM in renewable energy studies, and broadly in energy-monitoring devices tailored for other energy variables (e.g., hydro and wind energy).

ACS Style

Anh Ngoc-Lan Huynh; Ravinesh C. Deo; Duc-Anh An-Vo; Mumtaz Ali; Nawin Raj; Shahab Abdulla. Near Real-Time Global Solar Radiation Forecasting at Multiple Time-Step Horizons Using the Long Short-Term Memory Network. Energies 2020, 13, 3517 .

AMA Style

Anh Ngoc-Lan Huynh, Ravinesh C. Deo, Duc-Anh An-Vo, Mumtaz Ali, Nawin Raj, Shahab Abdulla. Near Real-Time Global Solar Radiation Forecasting at Multiple Time-Step Horizons Using the Long Short-Term Memory Network. Energies. 2020; 13 (14):3517.

Chicago/Turabian Style

Anh Ngoc-Lan Huynh; Ravinesh C. Deo; Duc-Anh An-Vo; Mumtaz Ali; Nawin Raj; Shahab Abdulla. 2020. "Near Real-Time Global Solar Radiation Forecasting at Multiple Time-Step Horizons Using the Long Short-Term Memory Network." Energies 13, no. 14: 3517.

Journal article
Published: 22 January 2019 in European Journal of Agronomy
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Seasonal climate forecasts (SCFs) have potential to improve productivity and profitability in the sugar industry. However, they are often underutilised due to insufficient evidence of the economic value of the forecasts, especially when there is a level of uncertainty associated with SCFs. Here, we demonstrate the value of integrating SCFs at various forecast quality (skill) levels into seasonal irrigation planning for sugarcane farming. A seasonal forecast system based on ENSO (El Niño Southern Oscillation) phases was parameterised by forecast quality to predict seasonal precipitation tercile (i.e. wet, neutral and dry) categories. A bio-economic model was developed to determine water-yield-profit relationships. Sugarcane production under different climatic conditions and irrigation scheduling scenarios was simulated using the Agricultural Production Systems sIMulator (APSIM)-Sugar, calibrated using case study information from one of Australia’s major irrigated sugarcane growing regions. We then employed an expected profit approach to achieve an optimal profit, rather than the more conventional optimal yield, for plant and ratoon crops to quantify the potential value of using SCFs in sugarcane irrigation decision making. The results show that using skilled SCF systems in sugarcane irrigation decision making can help growers improve their gross margin compared to that achieved in the absence of climate information (economic value). With a perfect forecast of moderate climatic conditions, an average economic value of up to AUD 27 ha−1 per annum was achieved, while forecasts of moderate wet or dry conditions indicated gains of up to AUD 40 and 43 ha−1 per annum, respectively, and forecasts of extreme wet or dry conditions delivered economic gains of up to AUD 150 and 260 ha−1 per annum, respectively. With the current seasonal climate forecast skill of 60% (based on the ENSO phases forecasting system) in the case study region, an average gain of up to AUD 4.5 ha−1 per annum was realised, with up to AUD 6.2 and 7.1 ha−1 per annum, respectively, for moderate wet and dry forecasting and up to AUD 92 and 43 ha−1 per annum, respectively, for extreme wet and dry forecasting. Improvements in the skill and reliability of SCFs will be important for achieving greater productivity and/or profitability and the wider uptake of climate forecasts in agricultural decision making.

ACS Style

Duc-Anh An-Vo; Shahbaz Mushtaq; Kathryn Reardon-Smith; Louis Kouadio; Steve Attard; David Cobon; Roger Stone. Value of seasonal forecasting for sugarcane farm irrigation planning. European Journal of Agronomy 2019, 104, 37 -48.

AMA Style

Duc-Anh An-Vo, Shahbaz Mushtaq, Kathryn Reardon-Smith, Louis Kouadio, Steve Attard, David Cobon, Roger Stone. Value of seasonal forecasting for sugarcane farm irrigation planning. European Journal of Agronomy. 2019; 104 ():37-48.

Chicago/Turabian Style

Duc-Anh An-Vo; Shahbaz Mushtaq; Kathryn Reardon-Smith; Louis Kouadio; Steve Attard; David Cobon; Roger Stone. 2019. "Value of seasonal forecasting for sugarcane farm irrigation planning." European Journal of Agronomy 104, no. : 37-48.

Journal article
Published: 10 January 2019 in Land Use Policy
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Water trading has become a key water scarcity risk-management tool for irrigators. Effective and enduring water trade systems require approaches that can cope with dynamic complexity and enable the inclusion of multiple stakeholders. Previous efforts to improve water trade systems have largely focused on reductionist approaches, which examine system components in isolation neglecting their interconnected nature. Such approaches to water trade system assessment are at risk of maladaptation resulting in increased market inefficiencies, transaction costs and market failure through barriers to participation. Using a systems thinking approach, we develop a conceptual model of a generalised water trade system in Australia’s Murray-Darling Basin (MDB or the Basin). The model visualises the Basin's water trade systems as a whole and identifies feedback mechanisms likely to influence trade development and endurance. We argue that such a conceptual model provides an effective communication tool for achieving a better understanding of market dynamics and alignment of stakeholder priorities to improve enduring market use. It can also serve as an assessment/evaluation tool for water trade policy and identify key leverage points for systemic interventions.

ACS Style

Thanh Mai; Shahbaz Mushtaq; Adam Loch; K. Reardon-Smith; Duc-Anh An-Vo. A systems thinking approach to water trade: Finding leverage for sustainable development. Land Use Policy 2019, 82, 595 -608.

AMA Style

Thanh Mai, Shahbaz Mushtaq, Adam Loch, K. Reardon-Smith, Duc-Anh An-Vo. A systems thinking approach to water trade: Finding leverage for sustainable development. Land Use Policy. 2019; 82 ():595-608.

Chicago/Turabian Style

Thanh Mai; Shahbaz Mushtaq; Adam Loch; K. Reardon-Smith; Duc-Anh An-Vo. 2019. "A systems thinking approach to water trade: Finding leverage for sustainable development." Land Use Policy 82, no. : 595-608.

Journal article
Published: 01 December 2018 in Journal of Hydrology
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ACS Style

Tai Nguyen-Ky; Shahbaz Mushtaq; Adam Loch; Kate Reardon-Smith; Duc-Anh An-Vo; Duc Ngo-Cong; Thanh Tran-Cong. Predicting water allocation trade prices using a hybrid Artificial Neural Network-Bayesian modelling approach. Journal of Hydrology 2018, 567, 781 -791.

AMA Style

Tai Nguyen-Ky, Shahbaz Mushtaq, Adam Loch, Kate Reardon-Smith, Duc-Anh An-Vo, Duc Ngo-Cong, Thanh Tran-Cong. Predicting water allocation trade prices using a hybrid Artificial Neural Network-Bayesian modelling approach. Journal of Hydrology. 2018; 567 ():781-791.

Chicago/Turabian Style

Tai Nguyen-Ky; Shahbaz Mushtaq; Adam Loch; Kate Reardon-Smith; Duc-Anh An-Vo; Duc Ngo-Cong; Thanh Tran-Cong. 2018. "Predicting water allocation trade prices using a hybrid Artificial Neural Network-Bayesian modelling approach." Journal of Hydrology 567, no. : 781-791.

Journal article
Published: 01 August 2018 in Ecological Economics
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Breeding for improved reproductive frost tolerance could allow greater yield and economic benefits to be achieved by (i) reducing direct frost damage and (ii) allowing earlier sowing to reduce risks of late-season drought and/or heat stresses. We integrated APSIM-Wheat simulations with economic modelling to evaluate economic benefits of virtual genotypes with different levels of frost tolerance for the Australian wheatbelt. Results highlighted substantial potential national economic benefits, with estimated industry profit increasing by (i) more than 55% for virtual genotypes with improved frost tolerance in silico, by (ii) 115% when sowing date was optimised for virtual frost-tolerant genotypes, and by (iii) an extra 35% (i.e. 150% in total) when using optimal nitrogen application. The total benefit potential was estimated at AUD 1890 million per annum if all these improvements could be combined. Regional benefits varied. In the West, the main benefits arose from improved frost tolerance reducing losses due to direct frost damage and applying additional nitrogen. In the East, earlier sowing allowed by tolerant genotypes resulted in large economic benefit. Overall, the analysis suggests significant economic benefits to the Australian wheat industry, should a source of frost tolerance be found.

ACS Style

Duc-Anh An-Vo; Shahbaz Mushtaq; Bangyou Zheng; Jack T. Christopher; Scott C. Chapman; Karine Chenu. Direct and Indirect Costs of Frost in the Australian Wheatbelt. Ecological Economics 2018, 150, 122 -136.

AMA Style

Duc-Anh An-Vo, Shahbaz Mushtaq, Bangyou Zheng, Jack T. Christopher, Scott C. Chapman, Karine Chenu. Direct and Indirect Costs of Frost in the Australian Wheatbelt. Ecological Economics. 2018; 150 ():122-136.

Chicago/Turabian Style

Duc-Anh An-Vo; Shahbaz Mushtaq; Bangyou Zheng; Jack T. Christopher; Scott C. Chapman; Karine Chenu. 2018. "Direct and Indirect Costs of Frost in the Australian Wheatbelt." Ecological Economics 150, no. : 122-136.

Journal article
Published: 01 August 2018 in European Journal of Agronomy
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Twelve large-scale climate drivers are employed to investigate their spatio-temporal influence on the variability of seasonal wheat yield in five major wheat-producing states across Australia using data for the period 1983–2013. Generally, the fluctuations in the Indian Ocean appear to have a dominant effect on the Australian wheat crop in all states except Western Australia, while the impact of oceanic conditions in the Pacific region is much stronger in Queensland. The results show a statistically significant negative correlation between the Indian Ocean Dipole (IOD) and the anomalous wheat yield in the early growing stage of the crop in the eastern and southeastern wheat belt regions. This correlation suggests that the wheat yield can be skillfully forecast 3–6 months ahead, supporting early decision-making in regard to precision agriculture. In this study, we use vine copula models to capture climate-yield dependence structures, including the occurrence of extreme events (i.e., the tail dependences). The co-occurrence of extreme events is likely to enhance the impacts of climate mode and this can be quantified probabilistically through conditional copula-based models. Generally, the developed D-vine quantile regression model provide greater accuracy for the forecasting of wheat yield at given different confidence levels compared to the traditional linear quantile regression (LQR) method. A five-fold cross-validation approach is also used to estimate the out-of-sample accuracy of both copula-statistical forecasting models. These findings provide a comprehensive analysis of the spatio-temporal impacts of different climate mode indices on Australian wheat crops. Improved quantification of the impacts of large-scale climate drivers on the wheat yield can allow a development of suitable planning processes and crop production strategies designed to optimize the yield and agricultural profit.

ACS Style

Thong Nguyen-Huy; Ravinesh C Deo; Shahbaz Mushtaq; Duc-Anh An-Vo; Shahjahan Khan. 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 2018, 98, 65 -81.

AMA Style

Thong Nguyen-Huy, Ravinesh C Deo, Shahbaz Mushtaq, Duc-Anh An-Vo, Shahjahan Khan. 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. 2018; 98 ():65-81.

Chicago/Turabian Style

Thong Nguyen-Huy; Ravinesh C Deo; Shahbaz Mushtaq; Duc-Anh An-Vo; Shahjahan Khan. 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, no. : 65-81.

Journal article
Published: 01 November 2017 in Field Crops Research
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ACS Style

Shahbaz Mushtaq; Duc-Anh An-Vo; Mandy Christopher; Bangyou Zheng; Karine Chenu; Scott C. Chapman; Jack T. Christopher; Roger C. Stone; Troy M. Frederiks; G.M. Monirul Alam. Economic assessment of wheat breeding options for potential improved levels of post head-emergence frost tolerance. Field Crops Research 2017, 213, 75 -88.

AMA Style

Shahbaz Mushtaq, Duc-Anh An-Vo, Mandy Christopher, Bangyou Zheng, Karine Chenu, Scott C. Chapman, Jack T. Christopher, Roger C. Stone, Troy M. Frederiks, G.M. Monirul Alam. Economic assessment of wheat breeding options for potential improved levels of post head-emergence frost tolerance. Field Crops Research. 2017; 213 ():75-88.

Chicago/Turabian Style

Shahbaz Mushtaq; Duc-Anh An-Vo; Mandy Christopher; Bangyou Zheng; Karine Chenu; Scott C. Chapman; Jack T. Christopher; Roger C. Stone; Troy M. Frederiks; G.M. Monirul Alam. 2017. "Economic assessment of wheat breeding options for potential improved levels of post head-emergence frost tolerance." Field Crops Research 213, no. : 75-88.

Journal article
Published: 01 September 2017 in Agricultural Water Management
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ACS Style

Thong Nguyen-Huy; Ravinesh C. Deo; Duc-Anh An-Vo; Shahbaz Mushtaq; Shahjahan Khan. Copula-statistical precipitation forecasting model in Australia’s agro-ecological zones. Agricultural Water Management 2017, 191, 153 -172.

AMA Style

Thong Nguyen-Huy, Ravinesh C. Deo, Duc-Anh An-Vo, Shahbaz Mushtaq, Shahjahan Khan. Copula-statistical precipitation forecasting model in Australia’s agro-ecological zones. Agricultural Water Management. 2017; 191 ():153-172.

Chicago/Turabian Style

Thong Nguyen-Huy; Ravinesh C. Deo; Duc-Anh An-Vo; Shahbaz Mushtaq; Shahjahan Khan. 2017. "Copula-statistical precipitation forecasting model in Australia’s agro-ecological zones." Agricultural Water Management 191, no. : 153-172.

Review
Published: 11 May 2016 in International Journal of Mineral Processing
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Flotation in mechanically agitated cells has been the workhorse of the mining industry, but our quantitative understanding of the effect of microturbulence generated by agitation on flotation is still very limited. This paper aims to review the literature on quantifying the microturbulence effects on bubble-particle interactions in flotation. The particular focus is on the stochastic description of bubble-particle interactions in the turbulent flow which is a random field. We briefly review the stochastic description of microturbulence and motions of particles of micrometre sizes and bubbles of millimetre sizes in the isotropic turbulence of mechanical flotation cells. The key starting point is the generic equation of motion, which can be decomposed into the mean turbulent variables and fluctuating turbulent variables. The turbulent flow of the carrying liquid is characterised using isotropic turbulence theory. The next focus is on reviewing bubble-particle turbulent collision and detachment interactions. Bubble-particle turbulent collision is poorly quantified; no quantitative models of the bubble-particle turbulent collision efficiency relevant for flotation are available. Current theories on bubble-particle turbulent detachment face some deficiencies. In assessing the microturbulence effect on bubble-particle detachment, the majority of studies only considers the particle acceleration in the centrifugal direction but ignore the transverse acceleration of particles, which is due to turbulent shear flow. Critically, contact angle required in quantifying the detachment is not constant, single-valued as considered in the theories, but can vary from receding to advancing value during the relaxation of the triple contact line on the particle surface. The latest experiments show that multiple-valued contact angle can significantly affect stability and detachment of floating particles. Finally, quantifying the microturbulence effect on flotation requires further research.

ACS Style

Anh V. Nguyen; Duc-Anh An-Vo; Thanh Tran-Cong; Geoffrey M. Evans. A review of stochastic description of the turbulence effect on bubble-particle interactions in flotation. International Journal of Mineral Processing 2016, 156, 75 -86.

AMA Style

Anh V. Nguyen, Duc-Anh An-Vo, Thanh Tran-Cong, Geoffrey M. Evans. A review of stochastic description of the turbulence effect on bubble-particle interactions in flotation. International Journal of Mineral Processing. 2016; 156 ():75-86.

Chicago/Turabian Style

Anh V. Nguyen; Duc-Anh An-Vo; Thanh Tran-Cong; Geoffrey M. Evans. 2016. "A review of stochastic description of the turbulence effect on bubble-particle interactions in flotation." International Journal of Mineral Processing 156, no. : 75-86.

Journal article
Published: 17 March 2015 in Water Resources Management
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Uncertainty and shortages of surface water supplies, as a result of global climate change, necessitate development of groundwater in many canal commands. Groundwater can be expensive to pump, but provides a reliable supply if managed sustainably. Groundwater can be used optimally in conjunction with surface water supplies. The use of such conjunctive systems can significantly decrease the risk associated with a stochastic availability of surface water supply. However, increasing pumping cost due to groundwater drawdown and energy prices are key concerns. We propose an innovative nonlinear programing model for the optimisation of profitability and productivity in an irrigation command area, with conjunctive water use options. The model, rather than using exogenous yields and gross margins, uses crop water production and profit functions to endogenously determine yields and water uses, and associated gross margins, respectively, for various conjunctive water use options. The model allows the estimation of the potential economic benefits of conjunctive water use and derives an optimal use of regional level land and water resources by maximising the net benefits and water productivity under various physical and economic constraints, including escalating energy prices. The proposed model is applied to the Coleambally Irrigation Area (CIA) in southeastern Australia to explore potential of conjunctive water use and evaluate economic implication of increasing energy prices. The results show that optimal conjunctive water use can offer significant economic benefit especially at low levels of surface water allocation and pumping cost. The results show that conjunctive water use potentially generates additional AUD 57.3 million if groundwater price is the same as surface water price. The benefit decreases significantly with increasing pumping cost.

ACS Style

D.-A. An-Vo; S. Mushtaq; T. Nguyen-Ky; J. Bundschuh; T. Tran-Cong; T. N. Maraseni; K. Reardon-Smith. Nonlinear Optimisation Using Production Functions to Estimate Economic Benefit of Conjunctive Water Use for Multicrop Production. Water Resources Management 2015, 29, 2153 -2170.

AMA Style

D.-A. An-Vo, S. Mushtaq, T. Nguyen-Ky, J. Bundschuh, T. Tran-Cong, T. N. Maraseni, K. Reardon-Smith. Nonlinear Optimisation Using Production Functions to Estimate Economic Benefit of Conjunctive Water Use for Multicrop Production. Water Resources Management. 2015; 29 (7):2153-2170.

Chicago/Turabian Style

D.-A. An-Vo; S. Mushtaq; T. Nguyen-Ky; J. Bundschuh; T. Tran-Cong; T. N. Maraseni; K. Reardon-Smith. 2015. "Nonlinear Optimisation Using Production Functions to Estimate Economic Benefit of Conjunctive Water Use for Multicrop Production." Water Resources Management 29, no. 7: 2153-2170.