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Prof. Dr. Shahbaz Mushtaq
Centre for Applied Climate Sciences, University of Southern Queensland, Toowoomba QLD 4350, Australia

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0 Food Security
0 Resilience
0 water management
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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: 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.

Article
Published: 02 March 2020 in Climatic Change
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Climate change will significantly impact the future viability and security of food production systems, with increased frequency and intensity of droughts, floods, storms and other extreme climatic events predicted in many regions. In order for food production systems to remain viable and resilient under a changing climate, novel approaches, which integrate risk management (i.e. adaptation) and risk transfer strategies, such as insurance, are required. We argue that the coordinated integration of risk management and risk transfer approaches will support greater resilience of food production systems under climate change. Conversely, if risk management and risk transfer strategies are not carefully integrated, there is potential to undermine adaptive capacity (e.g. insurance subsidies may dissuade farmers from investing in climate adaptation) and ultimately reduce the capacity of food production systems to cope with and recover from the adverse impacts of climate change. Here we propose a resilience-based conceptual framework for integrating risk management and risk transfer strategies along with four key principles, which we believe could underlie their successful integration and thus enhance food production system resilience under climate change. These are as follows: (1) pro-active investments in farmer climate adaptation rather than re-active disaster relief, (2) structuring of government subsidies around insurance and climate disaster relief to incentivise farmer climate adaptation, (3) rewarding farmer efforts towards climate adaptation with cheaper insurance premiums for those farmers that invest resources into climate adaptation and (4) recognising investments in the integration of farm climate adaptation and risk transfer schemes within the broader context of future climate disaster risk management and global food security. Such an integrated investment approach could substantially reduce future economic losses for farmers while also enhancing food security under climate change.

ACS Style

Shahbaz Mushtaq; Jarrod Kath; Roger Stone; Ross Henry; Peter Läderach; Kathryn Reardon-Smith; David Cobon; Torben Marcussen; Neil Cliffe; Paul Kristiansen; Frederik Pischke. Creating positive synergies between risk management and transfer to accelerate food system climate resilience. Climatic Change 2020, 161, 465 -478.

AMA Style

Shahbaz Mushtaq, Jarrod Kath, Roger Stone, Ross Henry, Peter Läderach, Kathryn Reardon-Smith, David Cobon, Torben Marcussen, Neil Cliffe, Paul Kristiansen, Frederik Pischke. Creating positive synergies between risk management and transfer to accelerate food system climate resilience. Climatic Change. 2020; 161 (3):465-478.

Chicago/Turabian Style

Shahbaz Mushtaq; Jarrod Kath; Roger Stone; Ross Henry; Peter Läderach; Kathryn Reardon-Smith; David Cobon; Torben Marcussen; Neil Cliffe; Paul Kristiansen; Frederik Pischke. 2020. "Creating positive synergies between risk management and transfer to accelerate food system climate resilience." Climatic Change 161, no. 3: 465-478.

Journal article
Published: 30 August 2019 in Agronomy
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Assessing and prescribing fertilizer use is critical to profitable and sustainable coffee production, and this is becoming a priority concern for the Robusta coffee industry. In this study, annual survey data of 798 farms across selected Robusta coffee-producing provinces in Vietnam and Indonesia between 2008 and 2017 were used to comparatively assess the fertilizer management strategies in these countries. Specifically, we aimed to characterize fertilizer use patterns in the key coffee-growing provinces and discuss the potential for improving nutrient management practices. Four types of chemical (NPK, super phosphate, potassium chloride and urea) and two of natural (compost and lime) fertilizers were routinely used in Vietnam. In Indonesia, NPK and urea were supplemented only with compost. Farmers in Vietnam applied unbalanced quantities of chemical fertilizers (i.e., higher rates than recommended) and at a constant rate between years whereas Indonesian farmers applied well below the recommended rates because of poor accessibility and financial support. The overuse of chemical fertilizers in Vietnam threatens the sustainability of Robusta coffee farming. Nevertheless, there is a potential for improvement in both countries in terms of nutrient management and sustainability of Robusta coffee production by adopting the best local fertilizer management practices.

ACS Style

Vivekananda Byrareddy; Louis Kouadio; Shahbaz Mushtaq; Roger Stone. Sustainable Production of Robusta Coffee under a Changing Climate: A 10-Year Monitoring of Fertilizer Management in Coffee Farms in Vietnam and Indonesia. Agronomy 2019, 9, 499 .

AMA Style

Vivekananda Byrareddy, Louis Kouadio, Shahbaz Mushtaq, Roger Stone. Sustainable Production of Robusta Coffee under a Changing Climate: A 10-Year Monitoring of Fertilizer Management in Coffee Farms in Vietnam and Indonesia. Agronomy. 2019; 9 (9):499.

Chicago/Turabian Style

Vivekananda Byrareddy; Louis Kouadio; Shahbaz Mushtaq; Roger Stone. 2019. "Sustainable Production of Robusta Coffee under a Changing Climate: A 10-Year Monitoring of Fertilizer Management in Coffee Farms in Vietnam and Indonesia." Agronomy 9, no. 9: 499.

Journal article
Published: 12 April 2019 in Climate Risk Management
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Wheat is key global food crop that is heavily influenced by climatic variability. There has been extensive research on improving forecasts and management practices to minimise climate related yield losses, but less on how to handle yield losses caused by climate variability. We investigated whether index insurance could be used to manage climate related losses, specifically from winter rainfall drought for wheat crops in Australia. We utilised 31 years of yield data from 15 of Australia’s key wheat producing regions. The winter rainfall index was developed and tested using generalised additive regression models, allowing for non-linear effects. Models with the winter rainfall index explained significant variation in wheat yields in each of the regions assessed. Wheat yield models had cross-validated R2’s >0.5 for two-thirds of the 15 regions modelled and best explained wheat yields in the Mallee, Western Australia (cross-validated R2 of 0.70). Calculated fair premiums ranged from $8.62 to $77.1 AUD/ha, while maximum liability was $59.25 to $212.12 AUD/ha. Throughout the eastern most wheat growing regions the winter rainfall index was consistently inefficient (i.e. not beneficial). In contrast, the winter rainfall index was financially efficient (i.e. beneficial) in the western wheat regions of eastern Australia and parts of Western Australia, with benefits of up to $97 AUD/ha and loss reductions of $9 AUD/ha. The spatial variability in insurance efficiency was explained by rainfall variance. As rainfall variance increased the efficiency of the winter rainfall index insurance for wheat decreased. Our findings have two important policy implications; (1) in areas where climate change is anticipated to increase rainfall variability risk-transfer options, such as index insurance, may become less viable and as such policies that support the development of index insurance without acknowledging or adjusting for variability in its benefit could lead to inefficient outcomes for both government and agricultural producers; and (2) where index rainfall insurance is not efficient then greater emphasise may need to be placed on developing alternate types of index insurance (e.g. using satellites) and / or on risk-management and climate adaptation strategies that minimise losses.

ACS Style

Jarrod Kath; Shahbaz Mushtaq; Ross Henry; Adewuyi Ayodele Adeyinka; Roger Stone; Torben Marcussen; Louis Kouadio. Spatial variability in regional scale drought index insurance viability across Australia’s wheat growing regions. Climate Risk Management 2019, 24, 13 -29.

AMA Style

Jarrod Kath, Shahbaz Mushtaq, Ross Henry, Adewuyi Ayodele Adeyinka, Roger Stone, Torben Marcussen, Louis Kouadio. Spatial variability in regional scale drought index insurance viability across Australia’s wheat growing regions. Climate Risk Management. 2019; 24 ():13-29.

Chicago/Turabian Style

Jarrod Kath; Shahbaz Mushtaq; Ross Henry; Adewuyi Ayodele Adeyinka; Roger Stone; Torben Marcussen; Louis Kouadio. 2019. "Spatial variability in regional scale drought index insurance viability across Australia’s wheat growing regions." Climate Risk Management 24, no. : 13-29.

Journal article
Published: 01 April 2019 in Journal of Environmental Management
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Depletion of groundwater resources is of increasing concern in many parts of the world; however, farmers' perceptions of resource status and the role these have in influencing decisions about groundwater use are rarely considered and even more rarely analysed. This paper investigates the links between farmers' perceptions of resource condition and drivers of groundwater decline and patterns of groundwater use in the semi-arid highland region of Balochistan, Pakistan. Key factors associated with groundwater over-exploitation in this region, identified by farmers, include: high returns from irrigated fruit and vegetable cultivation; drought; mass installation of tubewells; inefficient irrigation practices; government policies and subsidies that promote groundwater development; and lack of effective groundwater governance. Critically, while a majority of farmers in this study believe that groundwater is a limited resource, there is little evidence to indicate that this then leads to sustainable groundwater use decision making within these communities. Without effective intervention, groundwater resources in this region will potentially suffer the consequences of human behaviour associated with the use of common pool resources identified in Hardin's (1968) seminal 'Tragedy of the Commons' paper. This study exemplifies the importance to the future of rural communities in water scarce regions of effective governance, regulations and economic incentives for sustainable water management.

ACS Style

Syed Muhammad Khair; Shahbaz Mushtaq; Kate Reardon-Smith; Jenny Ostini. Diverse drivers of unsustainable groundwater extraction behaviour operate in an unregulated water scarce region. Journal of Environmental Management 2019, 236, 340 -350.

AMA Style

Syed Muhammad Khair, Shahbaz Mushtaq, Kate Reardon-Smith, Jenny Ostini. Diverse drivers of unsustainable groundwater extraction behaviour operate in an unregulated water scarce region. Journal of Environmental Management. 2019; 236 ():340-350.

Chicago/Turabian Style

Syed Muhammad Khair; Shahbaz Mushtaq; Kate Reardon-Smith; Jenny Ostini. 2019. "Diverse drivers of unsustainable groundwater extraction behaviour operate in an unregulated water scarce region." Journal of Environmental Management 236, no. : 340-350.

Original paper
Published: 26 February 2019 in Stochastic Environmental Research and Risk Assessment
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Development and implementation of advanced statistical models for analyzing stochastic dependencies of systemic weather risk can help farmers, agricultural policy-makers and financial agents to address potential risk adaptation strategies and mitigation of threats to the agricultural industry. This study develops copula-based statistical models to provide a better understanding of systemic weather risks with agricultural and weather event data from Australia. In particular, we adopt a C-vine approach to model the joint insurance losses caused by drought events occurring simultaneously across different locations, and consecutively in different growing seasons. This modelling approach is enriched by a clustering analysis process through the multidimensional Kruskal–Shephard scaling method. Daily rainfall data (1889–2012) recorded in sixteen meteorological stations across Australia’s wheat belt spanning different climatic conditions are employed. On a regional scale, droughts occurring in the west are more scattered during the October–December period and for April–June and October–December in the eastern, south-eastern and southern regions. On a national scale, drought events in the east are likely to spread out to the south-east and the south but not to the west. The results also reveal that the drought events in different seasons may not be perfectly correlated. Therefore, we conclude that spatial and temporal diversification strategies are likely to feasibly reduce the systemic weather risk in Australia. In particular, the average risk-reducing effect of the entire insured area across regional, national and temporal scales ranges between 0.62–0.94, 0.48–0.76, and 0.25–0.33, corresponding to 5%- (extreme drought) and 25%-quantiles (moderate drought). The findings suggest that diversifying risks over time is potentially more effective than spatial diversification. The outcomes may also act as an efficient tool for agricultural risk reduction, but simultaneously, it may also provide immensely useful information for suitable pricing of weather index-based insurance products.

ACS Style

Thong Nguyen-Huy; Ravinesh C. Deo; Shahbaz Mushtaq; Jarrod Kath; Shahjahan Khan. Copula statistical models for analyzing stochastic dependencies of systemic drought risk and potential adaptation strategies. Stochastic Environmental Research and Risk Assessment 2019, 33, 779 -799.

AMA Style

Thong Nguyen-Huy, Ravinesh C. Deo, Shahbaz Mushtaq, Jarrod Kath, Shahjahan Khan. Copula statistical models for analyzing stochastic dependencies of systemic drought risk and potential adaptation strategies. Stochastic Environmental Research and Risk Assessment. 2019; 33 (3):779-799.

Chicago/Turabian Style

Thong Nguyen-Huy; Ravinesh C. Deo; Shahbaz Mushtaq; Jarrod Kath; Shahjahan Khan. 2019. "Copula statistical models for analyzing stochastic dependencies of systemic drought risk and potential adaptation strategies." Stochastic Environmental Research and Risk Assessment 33, no. 3: 779-799.

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: 30 October 2018 in Computers and Electronics in Agriculture
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As a commodity for daily consumption, coffee plays a crucial role in the economy of several African, American and Asian countries; yet, the accurate prediction of coffee yield based on environmental, climatic and soil fertility conditions remains a challenge for agricultural system modellers. The ability of an Extreme Learning Machine (ELM) model to analyse soil fertility properties and to generate an accurate estimation of Robusta coffee yield was assessed in this study. The performance of 18 different ELM-based models with single and multiple combinations of the predictor variables based on the soil organic matter (SOM), available potassium, boron, sulphur, zinc, phosphorus, nitrogen, exchangeable calcium, magnesium, and pH, was evaluated. The ELM model’s performance was compared to that of existing predictive tools: Multiple Linear Regression (MLR) and Random Forest (RF). Individual model performance and inter-model performance comparisons were based on the root mean square error (RMSE), mean absolute error (MAE), Willmott’s Index (WI), Nash-Sutcliffe efficiency coefficient (ENS), and the Legates and McCabe’s Index (ELM) in the independent testing dataset. In the independent testing phase, an ELM model constructed with SOM, available potassium and available sulphur as predictor variables generated the most accurate coffee yield estimate (i.e., RMSE = 496.35 kg ha−1 or ±13.6%, and MAE = 326.40 kg ha−1 or ±7.9%). This contrasted with the less accurate MLR (RMSE = 1072.09 kg ha−1 and MAE = 797.60 kg ha−1) and RF (RMSE = 1087.35 kg ha−1 and MAE = 769.57 kg ha−1) model. Normalized metrics showed the ELM model’s ability to yield highly accurate results: WI = 0.9952, ENS = 0.406 and ELM = 0.431. In comparison to the MLR and RF models, the adoption of the ELM model as an improved class of artificial intelligence models for coffee yield prediction in smallholder farms in this study constitutes an original contribution to the agronomic sector, particularly with respect to the appropriate selection of most optimal soil properties that can be used in the prediction of optimal coffee yield. The potential utility of coupling artificial intelligence algorithms with biophysical-crop models (i.e., as a data-intelligent automation tool) in decision-support systems that implement precision agriculture, in an effort to improve yield in smallholder farms based on carefully screened soil fertility dataset was confirmed.

ACS Style

Louis Kouadio; Ravinesh C. Deo; Vivekananda Byrareddy; Jan F. Adamowski; Shahbaz Mushtaq; Van Phuong Nguyen. Artificial intelligence approach for the prediction of Robusta coffee yield using soil fertility properties. Computers and Electronics in Agriculture 2018, 155, 324 -338.

AMA Style

Louis Kouadio, Ravinesh C. Deo, Vivekananda Byrareddy, Jan F. Adamowski, Shahbaz Mushtaq, Van Phuong Nguyen. Artificial intelligence approach for the prediction of Robusta coffee yield using soil fertility properties. Computers and Electronics in Agriculture. 2018; 155 ():324-338.

Chicago/Turabian Style

Louis Kouadio; Ravinesh C. Deo; Vivekananda Byrareddy; Jan F. Adamowski; Shahbaz Mushtaq; Van Phuong Nguyen. 2018. "Artificial intelligence approach for the prediction of Robusta coffee yield using soil fertility properties." Computers and Electronics in Agriculture 155, no. : 324-338.

Journal article
Published: 25 October 2018 in Weather and Climate Extremes
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Managing the risks of climate variability on crop production is central to ensuring financially viable farming systems and sustainable food production. Insurance provides a mechanism to manage and transfer climate risks. However, traditional multi-peril crop insurance (MCPI) is often too expensive and so other methods, such as index insurance, are being explored as a cheaper way to insure farmers against climate induced crop losses. Here we investigate the potential financial benefits of index insurance (protecting against excessive rainfall) for agricultural producers, namely sugar cane farmers in Tully, northern Australia. We used 80 years of historical climate and yield data to develop an excessive rainfall index. The index was developed and tested using generalised additive regression models (allowing for non-linear effects) and quantile regression, which allows relationships with lower quantiles (i.e. low yield events) to be assessed. From the regression models we derived relationships between the excessive rainfall index and sugar cane yield losses that were converted to insurance fair premiums (i.e. premiums that cover expected losses). Finally, we used efficiency analysis, based on Conditional Tail Expectation (CTE), Certainty Equivalence of Revenue (CER) and Mean Root Square Loss (MRSL), to quantify financial benefits to farmers if they purchased excessive rainfall index insurance. The regression model predicted sugar cane yields well (cross-validated R2 of 0.65). The efficiency analysis indicated there could be financial benefit to sugar cane farmers if they were to use excessive rainfall index insurance. Index insurance (based on the assumption of a fair premium) could make farmers better off by $269.85 AUD/ha on average in years with excessive rainfall (i.e. years with rainfall over the 95th percentile). Index insurance could offer a viable method for managing the financial risks posed by excessive rainfall for sugar cane producers in northern Australia. We are not aware of any other study demonstrating the potential benefits of excessive rainfall index insurance in the literature, but our results suggest this type of insurance may be viable for sugar cane producers, and other crops, in parts of the world where extreme rainfall poses a risk to the financial sustainability of production.

ACS Style

Jarrod Kath; Shahbaz Mushtaq; Ross Henry; Adewuyi Adeyinka; Roger Stone. Index insurance benefits agricultural producers exposed to excessive rainfall risk. Weather and Climate Extremes 2018, 22, 1 -9.

AMA Style

Jarrod Kath, Shahbaz Mushtaq, Ross Henry, Adewuyi Adeyinka, Roger Stone. Index insurance benefits agricultural producers exposed to excessive rainfall risk. Weather and Climate Extremes. 2018; 22 ():1-9.

Chicago/Turabian Style

Jarrod Kath; Shahbaz Mushtaq; Ross Henry; Adewuyi Adeyinka; Roger Stone. 2018. "Index insurance benefits agricultural producers exposed to excessive rainfall risk." Weather and Climate Extremes 22, no. : 1-9.

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 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: 20 July 2018 in Weather and Climate Extremes
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An agricultural producer's crop yield and subsequent farming revenues are affected by many complex factors, including price fluctuations, government policy and climate (e.g., rainfall and temperature) extremes. Geographical diversification is identified as a potential farmer adaptation and decision support tool that could assist producers to reduce unfavourable financial impacts due to variabilities in crop price and yield, associated with climate variations. There has been limited research performed on the effectiveness of this strategy. The paper proposed a new statistical approach to investigate whether the geographical spread of wheat farm portfolios across three climate broad-acre (i.e., rain-fed) zones could potentially reduce financial risks for producers in Australian agro-ecological zones. A suite of popular and statistically robust tools applied in finance based on well-established statistical theories, comprised of the Conditional Value-at-Risk (CVaR) and the joint copula model were employed to evaluate the effectiveness geographical diversification. CVaR is utilised to benchmark the loss (i.e., downside risk), while the copula function is employed to model joint distribution among marginal returns (i.e., profit in each zone). The mean-CVaR optimisations indicate that geographical diversification could be a feasible agricultural risk management approach for wheat farm portfolio managers in achieving their optimised expected returns while controlling the risks (i.e., targeting levels of risk). Further, in this study, the copula-based mean-CVaR model is seen to better simulate extreme losses compared to the conventional multivariate-normal models, which underestimate the minimum risk levels at a given target of expected return. Among the suite of tested copula-based models, the vine copula in this study is found to be a superior in capturing the tail dependencies compared to the other multivariate copula models investigated.

ACS Style

Thong Nguyen-Huy; Ravinesh C. Deo; Shahbaz Mushtaq; Jarrod Kath; Shahjahan Khan. Copula-based agricultural conditional value-at-risk modelling for geographical diversifications in wheat farming portfolio management. Weather and Climate Extremes 2018, 21, 76 -89.

AMA Style

Thong Nguyen-Huy, Ravinesh C. Deo, Shahbaz Mushtaq, Jarrod Kath, Shahjahan Khan. Copula-based agricultural conditional value-at-risk modelling for geographical diversifications in wheat farming portfolio management. Weather and Climate Extremes. 2018; 21 ():76-89.

Chicago/Turabian Style

Thong Nguyen-Huy; Ravinesh C. Deo; Shahbaz Mushtaq; Jarrod Kath; Shahjahan Khan. 2018. "Copula-based agricultural conditional value-at-risk modelling for geographical diversifications in wheat farming portfolio management." Weather and Climate Extremes 21, no. : 76-89.

Journal article
Published: 01 June 2018 in Environmental Science & Policy
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G M Monirul Alam; Khorshed Alam; Shahbaz Mushtaq; Walter Leal Filho. How do climate change and associated hazards impact on the resilience of riparian rural communities in Bangladesh? Policy implications for livelihood development. Environmental Science & Policy 2018, 84, 7 -18.

AMA Style

G M Monirul Alam, Khorshed Alam, Shahbaz Mushtaq, Walter Leal Filho. How do climate change and associated hazards impact on the resilience of riparian rural communities in Bangladesh? Policy implications for livelihood development. Environmental Science & Policy. 2018; 84 ():7-18.

Chicago/Turabian Style

G M Monirul Alam; Khorshed Alam; Shahbaz Mushtaq; Walter Leal Filho. 2018. "How do climate change and associated hazards impact on the resilience of riparian rural communities in Bangladesh? Policy implications for livelihood development." Environmental Science & Policy 84, no. : 7-18.

Research article
Published: 31 May 2018 in Information Development
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Access to information and communication technology (ICT) has been considered crucial to alleviate poverty and improve food security of rural households. The mobile phone is an ICT that is widely used by rural households in developing countries. This study examines the determinants of mobile phone adoption using survey data of vulnerable rural households in Bangladesh, a developing country; the study empirically assesses the income hypothesis of mobile phone adoption in particular. Four alternative specifications of the model are developed to test the stability and robustness of the estimates. The study finds rural households have heterogeneous access to ICT such as radio, TV, computer and the Internet except mobile phone. Our estimated Gini coefficient indicates high income inequality among the rural households. The model results suggest that household income positively influences mobile phone adoption. However, the impact is not statistically significant. Other factors such as respondents’ age, education and farm category are statistically significant influences on mobile phone adoption. An increasing use of mobile phones is likely to enhance the sharing of valuable information among rural households for the better management of their livelihoods and improved farming decisions.

ACS Style

G M Monirul Alam; Khorshed Alam; Shahbaz Mushtaq; Most Nilufa Khatun; M S Arifeen Khan Mamun. Influence of socio-demographic factors on mobile phone adoption in rural Bangladesh: Policy implications. Information Development 2018, 35, 739 -748.

AMA Style

G M Monirul Alam, Khorshed Alam, Shahbaz Mushtaq, Most Nilufa Khatun, M S Arifeen Khan Mamun. Influence of socio-demographic factors on mobile phone adoption in rural Bangladesh: Policy implications. Information Development. 2018; 35 (5):739-748.

Chicago/Turabian Style

G M Monirul Alam; Khorshed Alam; Shahbaz Mushtaq; Most Nilufa Khatun; M S Arifeen Khan Mamun. 2018. "Influence of socio-demographic factors on mobile phone adoption in rural Bangladesh: Policy implications." Information Development 35, no. 5: 739-748.

Research article
Published: 01 March 2018 in South Asia Economic Journal
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Despite improvements in food production, many rural households in Bangladesh are still food insecure, and this requires urgent policy intervention if the situation is to improve. This article examines the factors influencing food security of vulnerable rural riverine households in Bangladesh. The results reveal that riverine households’ lack of access to many basic necessities and services, such as food, safe drinking water, education and health, results in increased vulnerability to food insecurity which could lead to an unfortunate vicious cycle of poverty. Model results indicate that household heads’ education, household size, adoption of livestock and access to non-farm earnings also affect food security. More importantly, evidence suggests that access to improved health care also needs policy support in parallel with improved access to food to achieve and sustain long-term food security in Bangladesh. JEL: D130, E230, Q540, Q180

ACS Style

G.M. Monirul Alam; Khorshed Alam; Shahbaz Mushtaq. Drivers of Food Security of Vulnerable Rural Households in Bangladesh. South Asia Economic Journal 2018, 19, 43 -63.

AMA Style

G.M. Monirul Alam, Khorshed Alam, Shahbaz Mushtaq. Drivers of Food Security of Vulnerable Rural Households in Bangladesh. South Asia Economic Journal. 2018; 19 (1):43-63.

Chicago/Turabian Style

G.M. Monirul Alam; Khorshed Alam; Shahbaz Mushtaq. 2018. "Drivers of Food Security of Vulnerable Rural Households in Bangladesh." South Asia Economic Journal 19, no. 1: 43-63.

Journal article
Published: 01 January 2018 in Agricultural Water Management
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Allyson Williams; Shahbaz Mushtaq; Louis Kouadio; Brendan Power; Torben Marcussen; David McRae; Geoff Cockfield. An investigation of farm-scale adaptation options for cotton production in the face of future climate change and water allocation policies in southern Queensland, Australia. Agricultural Water Management 2018, 196, 124 -132.

AMA Style

Allyson Williams, Shahbaz Mushtaq, Louis Kouadio, Brendan Power, Torben Marcussen, David McRae, Geoff Cockfield. An investigation of farm-scale adaptation options for cotton production in the face of future climate change and water allocation policies in southern Queensland, Australia. Agricultural Water Management. 2018; 196 ():124-132.

Chicago/Turabian Style

Allyson Williams; Shahbaz Mushtaq; Louis Kouadio; Brendan Power; Torben Marcussen; David McRae; Geoff Cockfield. 2018. "An investigation of farm-scale adaptation options for cotton production in the face of future climate change and water allocation policies in southern Queensland, Australia." Agricultural Water Management 196, no. : 124-132.

Journal article
Published: 01 January 2018 in Climate Risk Management
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Shahbaz Mushtaq. Managing climate risks through transformational adaptation: Economic and policy implications for key production regions in Australia. Climate Risk Management 2018, 19, 48 -60.

AMA Style

Shahbaz Mushtaq. Managing climate risks through transformational adaptation: Economic and policy implications for key production regions in Australia. Climate Risk Management. 2018; 19 ():48-60.

Chicago/Turabian Style

Shahbaz Mushtaq. 2018. "Managing climate risks through transformational adaptation: Economic and policy implications for key production regions in Australia." Climate Risk Management 19, no. : 48-60.