Robusta coffee model: an integrated model for coffee production at a regional scale

The Vietnamese coffee industry is the world's second largest producer of coffee beans. The industry is significantly influenced by seasonal climate variations, water shortages, and extreme climatic events, especially drought. Given a 15% expected increase in global coffee demand and the potential adverse effects of projected climate variability, the success of the Vietnamese coffee industry depends heavily on minimising the risks along the supply chain and capitalising on potential opportunities. Advances in seasonal climate forecasts, when integrated with crop production systems, can greatly improve industry preparedness and productivity. We present the progress on the development of a ‘Robusta variety' coffee production model, an integrated forecasting system, which aims to provide coffee production estimate based on simulating coffee growth biophysical processes and seasonal climate forecast systems. The model uses daily values (such as daily minimum and maximum temperatures, solar radiation, and rainfall) and simulates the growth of the coffee tree (e.g. biomass) and the production of green beans. The initial simulated results are encouraging, however, while the model successfully picks up the climatic variability, the precision is not yet outstanding. Further refinement and improvement of the parametrization are ongoing to provide more reliable and comprehensive outputs at different lead times. While additional work is yet to be done the preliminary results look promising and show that seasonal climate and crop forecasting offers substantial benefits to coffee growers and industry through increased profitability, better logistical arrangements and preparedness for extreme events such as floods and droughts

Drought climate adaptation program: producing enhanced agricultural crop insurance systems: summary report

Queensland farmers are subject to highly variable climatic conditions, including drought and floods, which can undermine production. Insurance could play an important role in helping Queensland farmers manage their climate risk. However, currently, the use of insurance to manage climate-related production risk is poorly understood and utilised by farmers. This project aims to address this gap by providing information on climate risks and the role of insurance for managing these. This project conducted focused reviews on climate risk in agriculture and on how insurance products could be used to address these risks. The project also carried out on-ground surveys from cotton and sugar industry and conducted modelling to assess risks and the role of insurance for cotton and sugar cane farmers in Queensland. Prototype climate assessment risk and reporting tools were also developed. The reviews carried out in this project identified that Queensland’s agricultural sector is highly exposed to production volatility as a result of weather risks. It is our view that the Queensland agricultural sector has an excellent opportunity to provide its farmers with protection against uninsured seasonal risks to crop production. Key climate and farming systems risks were identified by interviewing a total of 55 farmers (23 cotton growers and 32 sugar cane growers) across Queensland. Key climate risks to the cotton industry include hail, drought/dry years (lack of rainfall during planting and season), quality downgrade (discolouration), excessive heat, floods and wet weather (during the season and especially during harvest). Similarly, for the sugar industry, key climate risks include drought, flood, excessive rainfall during harvest, cyclone, pests and disease. Key messages from farmer surveys are that current insurance products available to Queensland farmers (specifically, cotton and sugar cane farmers) may not address critical risks to the production and/or profitability of these systems and that farmers would prefer to have comprehensive insurance products available that cover them against profitability losses across multiple risk factors. Based on survey findings three prototype insurance products were developed for the cotton industry Insurance products developed were Drought Cover: insufficient rainfall during the planting season – August to November; Drought Cover: insufficient rainfall during growing season – November to February; and Wet Harvest Cover: excessive rainfall during harvest season – March to June. Two prototype insurance products were developed for the sugar industry. They include; Cyclone Cover: crop damage during cyclone season – November to April; and Wet Harvest Cover: excessive rainfall during harvest season – June to December Rainfall-indexed based worked examples were also developed for sugar and cotton industry growers

Drought climate adaptation program: producing enhanced agricultural crop insurance systems: final report

Queensland farmers are subject to highly variable climatic conditions, including drought and floods, which can undermine production. Insurance could play an important role in helping Queensland farmers manage their climate risk. However, currently the use of insurance to manage climate related production risk is poorly understood and utilised by farmers. This project aims to address this gap by providing information on climate risks and the role of insurance for managing these. This project conducted focussed reviews on climate risk in agriculture and on how insurance products could be used to address these risks. The project also carried out on-ground surveys from cotton and sugar industry and conducted modelling to assess risks and the role of insurance for cotton and sugar cane farmers in Queensland. Prototype climate assessment risk and reporting tools were also developed. The reviews carried out in this project identified that Queensland’s agricultural sector is highly exposed to production volatility as a result of weather risks. It is our view that the Queensland agricultural sector has an excellent opportunity to provide its farmers with protection against uninsured seasonal risks to crop production. Key climate and farming systems risks were identified by interviewing a total of 55 farmers (23 cotton growers and 32 sugar cane growers) across Queensland. Key climate risks to the cotton industry include hail, drought/dry years (lack of rainfall during planting and season), quality downgrade (discolouration), excessive heat, floods and wet weather (during season and especially during harvest). Similarly, for the sugar industry, key climate risks include, drought, flood, excessive rainfall during harvest, cyclone, pests and disease. Key messages from farmer surveys are that current insurance products available to Queensland farmers (specifically, cotton and sugar cane farmers) may not address critical risks to the production and/or profitability of these systems and that farmers would prefer to have comprehensive insurance products available that cover them against profitability losses across multiple risk factors. A ‘climate and agricultural risk assessment and reporting tool’ (prototype) was developed as part of the project. This ‘tool’ allows quantification of key climate risks, initially for the sugar and cotton industry. The tool provides an option to generate a detail climate risk report based on historical data and a future seasonal climate forecast for an individual location. The tool data also serves as a dataset portal, allowing for the download of data in a required template. Cotton and sugarcane crop models APSIM and DSSAT were employed to simulate the growth and yield for 10 and 12 sites, respectively, across Queensland over the period 1940-2017 for various crop management factors. Comparing the simulated yields (from each model or the mean simulated value from ensemble models) to the observed yield (available at regional scale) the trend in year to year variability is satisfactorily captured for cotton on average, whereas for sugarcane there is a trend to overestimate or underestimate the yield depending on the site. Based on survey findings three prototype insurance products were developed for the cotton industry Insurance products developed were Drought Cover: insufficient rainfall during the planting season – August to November; Drought Cover: insufficient rainfall during growing season – November to February; and Wet Harvest Cover: excessive rainfall during harvest season – March to June. Two prototype insurance products were developed for sugar industry. They include; Cyclone Cover: crop damage during cyclone season – November to April; and Wet Harvest Cover: excessive rainfall during harvest season – June to December. Rainfall-indexed based worked examples were also developed for sugar and cotton industry growers to better appreciate the insurance mechanisms

Drought climate adaptation program: producing enhanced agricultural crop insurance systems: final report

Queensland farmers are subject to highly variable climatic conditions, including drought and floods, which can undermine production. Insurance could play an important role in helping Queensland farmers manage their climate risk. However, currently the use of insurance to manage climate related production risk is poorly understood and utilised by farmers. This project aims to address this gap by providing information on climate risks and the role of insurance for managing these. This project conducted focussed reviews on climate risk in agriculture and on how insurance products could be used to address these risks. The project also carried out on-ground surveys from cotton and sugar industry and conducted modelling to assess risks and the role of insurance for cotton and sugar cane farmers in Queensland. Prototype climate assessment risk and reporting tools were also developed. The reviews carried out in this project identified that Queensland’s agricultural sector is highly exposed to production volatility as a result of weather risks. It is our view that the Queensland agricultural sector has an excellent opportunity to provide its farmers with protection against uninsured seasonal risks to crop production. Key climate and farming systems risks were identified by interviewing a total of 55 farmers (23 cotton growers and 32 sugar cane growers) across Queensland. Key climate risks to the cotton industry include hail, drought/dry years (lack of rainfall during planting and season), quality downgrade (discolouration), excessive heat, floods and wet weather (during season and especially during harvest). Similarly, for the sugar industry, key climate risks include, drought, flood, excessive rainfall during harvest, cyclone, pests and disease. Key messages from farmer surveys are that current insurance products available to Queensland farmers (specifically, cotton and sugar cane farmers) may not address critical risks to the production and/or profitability of these systems and that farmers would prefer to have comprehensive insurance products available that cover them against profitability losses across multiple risk factors. A ‘climate and agricultural risk assessment and reporting tool’ (prototype) was developed as part of the project. This ‘tool’ allows quantification of key climate risks, initially for the sugar and cotton industry. The tool provides an option to generate a detail climate risk report based on historical data and a future seasonal climate forecast for an individual location. The tool data also serves as a dataset portal, allowing for the download of data in a required template. Cotton and sugarcane crop models APSIM and DSSAT were employed to simulate the growth and yield for 10 and 12 sites, respectively, across Queensland over the period 1940-2017 for various crop management factors. Comparing the simulated yields (from each model or the mean simulated value from ensemble models) to the observed yield (available at regional scale) the trend in year to year variability is satisfactorily captured for cotton on average, whereas for sugarcane there is a trend to overestimate or underestimate the yield depending on the site. Based on survey findings three prototype insurance products were developed for the cotton industry Insurance products developed were Drought Cover: insufficient rainfall during the planting season – August to November; Drought Cover: insufficient rainfall during growing season – November to February; and Wet Harvest Cover: excessive rainfall during harvest season – March to June. Two prototype insurance products were developed for sugar industry. They include; Cyclone Cover: crop damage during cyclone season – November to April; and Wet Harvest Cover: excessive rainfall during harvest season – June to December. Rainfall-indexed based worked examples were also developed for sugar and cotton industry growers to better appreciate the insurance mechanisms

Стохастическое дифференциальное уравнение нейтрального типа в гильбертовом пространстве

Стохастические дифференциальные уравнени

Tropical cyclone insurance for Queensland agriculture

This report is for Queensland agricultural producers and related industries as well as local and state governments interested in insurance options that mitigate the financial risks associated with cyclones. The report outlines the risks and impacts of cyclones on the Queensland agricultural sector and the availability of insurance solutions to mitigate the financial consequences of such events. The cyclone insurance solutions outlined in this report are preliminary and the parameters and pricing will vary according to the location covered and as more data become available

A satellite-based Standardized Antecedent Precipitation Index (SAPI) for mapping extreme rainfall risk in Myanmar

In recent decades, substantial efforts have been devoted in flood monitoring, prediction, and risk analysis for aiding flood event preparedness plans and mitigation measures. Introducing an initial framework of spatially probabilistic analysis of flood research, this study highlights an integrated statistical copula and satellite data-based approach to modelling the complex dependence structures between flood event characteristics, i.e., duration (D), volume (V) and peak (Q). The study uses Global daily satellite-based Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) (spatial resolution of ∼5 km) during 1981–2019 to derive a Standardized Antecedence Precipitation Index (SAPI) and its characteristics through a time-dependent reduction function for Myanmar. An advanced vine copula model was applied to model joint distributions between flood characteristics for each grid cell. The southwest (Rakhine, Bago, Yangon, and Ayeyarwady) and south (Kayin, Mon, and Tanintharyi) regions are found to be at high risk, with a probability of up to 40% of flood occurrence in August and September in the south (Kayin, Mon, and Tanintharyi) and southwest regions (Rakhine, Bago, Yangon, and Ayeyarwady). The results indicate a strong correlation among flood characteristics; however, their mean and standard deviation are spatially different. The findings reveal significant differences in the spatial patterns of the joint exceedance probability of flood event characteristics in different combined scenarios. The probability that duration, volume, and peak concurrently exceed 50th-quantile (median) values are about 60–70% in the regions along the administrative borders of Chin, Sagaing, Mandalay, Shan, Nay Pyi Taw, and Keyan. In the worst case and highest risk areas, the probability that duration, volume, and peak exceed the extreme values, i.e., the 90th-quantile, about 10–15% in the southwest of Sagaing, southeast of Chin, Nay Pyi Taw, Mon and areas around these states and up to 30% in the southeast of Dekkhinathiri township (Nay Pyi Taw). The proposed approach could improve the evaluation of exceedance probabilities used for flood early warning and risk assessment and management. The proposed framework is also applicable at larger scales (e.g., regions, continents and globally) and in different hydrological design events and for risk assessments (e.g., insurance)

Virtual world technologies to enhance climate risk management on Australian sugar cane farms

Improved climate risk decision-making and management in agriculture is critical to the well-being and long-term sustainability of farming communities and future global food security. Decision-making on farms often makes assumptions about seasonal conditions and weather events over the cropping season. Projected climate change and increasing climate variability are likely to pose increasing challenges to the productivity and profitability of farming systems. Hence, better understanding of climate information may improve farmers' ability to plan for climate risk. Digital technologies offer an important alternative in the delivery and communication of agricultural information, complementing and expanding the reach of conventional face-to-face agricultural extension services, particularly where these are subject to declining levels of investment. Sophisticated digital platforms and their applications in learning environments also offer new opportunities which may influence and significantly enhance agricultural knowledge exchange. This paper reports on a project undertaken by the University of Southern Queensland's Australian Digital Futures Institute and International Centre for Applied Climate Sciences to develop and evaluate a web-based virtual 'discussion-support' system that integrates climate information with practical farming operations in Australian sugar farming systems. Customized video clips (machinima), created in the Second Life virtual world environment, use lifelike avatar actors to model conversations about climate risk and key farm operational decisions relevant to sugarcane farmers. Designed to be readily available online, this innovative approach is designed to provide more equitable and cost-effective access to targeted climate information as well as improved learning and decision-making opportunities at local, regional, national and even global scales

Virtual Discussions to Support Climate Risk Decision Making on Farms

Climate variability represents a significant risk to farming enterprises. Effective extension of climate information may improve climate risk decision making and adaptive management responses to climate variability on farms. This paper briefly reviews current agricultural extension approaches and reports stakeholder responses to new web-based virtual world ‘discussion-support’ tools developed for the Australian sugar cane farming industry. These tools incorporate current climate science and sugar industry better management practices, while leveraging the social-learning aspects of farming, to provide a stimulus for discussion and climate risk decision making. Responses suggest that such virtual world tools may provide effective support for climate risk decision making on Australian sugar cane farms. Increasing capacity to deliver such tools online also suggests potential to engage large numbers of farmers globally