Search

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 Nino 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.

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 values > 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. Keywords: Climate variability, Drought, Wheat, Risk transfer, Climate adaptation

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).

Frost, during reproductive developmental stages, especially post head emergence frost (PHEF), can result in catastrophic yield loss for wheat producers. Breeding for improved PHEF tolerance may allow greater yield to be achieved, by (i) reducing direct frost damage and (ii) facilitating earlier crop sowing to reduce the risk of late-season drought and/or heat stress. This paper provides an economic feasibility analysis of breeding options for PHEF tolerant wheat varieties. It compares the economic benefit to growers with the cost of a wheat breeding program aimed at developing PHEF tolerant varieties. The APSIM wheat model, with a frost-impact and a phenology gene-based module, was employed to simulate direct and indirect yield benefits for various levels of improved frost tolerance. The economic model considers optimal profit, based on sowing date and nitrogen use, rather than achieving maximum yield. The total estimated fixed cost of breeding program was AUD 1293 million, including large scale seed production to meet seed demand, with AUD 1.2 million year −1 to run breeding program after advanced development and large scale field experiments. The results reveal that PHEF tolerant varieties would lead to a significant increase in economic benefits through reduction in direct damage and an increase in yield through early sowing. The economic benefits to growers of up to AUD 4841 million could be realised from growing PHEF tolerant lines if useful genetic variation can be found. Sensitivity analyses indicated that the benefits are particularly sensitive to increases in fixed costs, seed replacement, discount rate, and to delays in variety release. However, the investment still remains viable for most tested scenarios. Based on comparative economic benefits, if breeders were able to develop PHEF tolerant varieties that could withstand cold temperatures −4 °C below the current damage threshold, there is very little further economic value of breeding total frost tolerant varieties.

The Earth’s climate and changes to it impact our lives, well-being and economy in numerous ways, some positive and some negative. Managing the risks that arise from changes in the climate over the coming months, years and decades is one of the most pressing challenges that society faces, but there are also some opportunities. The provision and use of climate information in decision-making (i.e. climate services) are central to managing the risks and opportunities. In this article we describe the seemingly complex climate service landscape, the actors in it, what the services are used for, and what next, to help stimulate further action to enable society to reduce risks and realise benefits, particularly timely as the world looks ahead to build a green recovery from the COVID-19 pandemic on the path to net zero emissions. Through a consideration of the value chain for climate services, we emphasise the importance of dialogue and collaboration between those developing, providing and using climate information in decision-making, and stress that a climate service is only worth delivering if it is going to be used by someone to influence an outcome. Co-production can be highly useful for enabling the dialogue and collaborating across the value chain, helping create services based on credible, salient and legitimate knowledge.

Robusta coffee is critically important for the economy and farmers of Vietnam, but also requires substantial irrigation leading to dwindling water resources. Developing clear recommendations for improved irrigation water management, while maintaining or increasing yield is therefore a key knowledge need for the coffee industry. We analyse 10-cropping-year data (2008/2009–2017/2018) of 558 farms across four major coffee-producing provinces in Vietnam’s Central Highlands using CROPWAT and hierarchical Bayesian modelling to (1) identify irrigation requirements under different climatic conditions, and (2) investigate the potential for improved irrigation management strategies. In average rainfall years the majority of farmers in Dak Nong and Lam Dong supplied an equivalent of 455–909 L tree−1 (assuming 1100 plants ha−1) with corresponding average yields ranging from 2149 to 3177 kg ha−1. In Dak Lak and Gia Lai the predominant range was equivalent to 1364–1818 L tree-1 (corresponding average yields: 2190 to 3203 kg ha−1). In dry years more water was supplied through irrigation at various levels depending on the province: varying between 1364–1818 L tree−1 in Dak Lak and Gia Lai, and 909–1364 L tree−1 in Dak Nong and Lam Dong. Our study also shows that irrigation water can be reduced by 273–536 L tree−1 (300–590 m3 ha−1) annually from the current levels in average rainfall years while still achieving average yield levels greater than 3000 kg ha−1. In dry years reductions of 27–218 L tree−1 (30–240 m3 ha−1) are possible. With adequate management of the key crop practices affecting coffee yields, substantial water savings at the provincial scale could be achieved. Thus, our findings could serve as a basis for province-specific irrigation water management in robusta coffee farms that will not only reduce overall water use, but also potentially maintain satisfactory yield levels.

Recent years have seen a growing recognition of and attention to strengthening community flood resilience as a key leverage for achieving sustainable flood risk management. The literature on the success of focusing on ex-post responses to flood events shows poor outcomes in mitigating flood risks across the board. Here, we employ systems thinking to conceptualise the dynamics underlying interactions among endogenous characteristics of the flood-prone community, and apply this, as a case study example, to the regional township of Roma in inland Queensland, Australia—a location that has experienced significant flooding in recent decades. Our results show that current flood mitigation policies are likely to be maladaptive due to unintended consequences that ultimately undermine the effectiveness of the interventions in the longer term. Based on our analysis, we conclude that integrated flood risk management, effected through well-targeted proactive investments—such as investment in infrastructure; technology advances; capacity improvements; shifts in systems, management practices and behaviour—and risk transfer (insurance) options, provide opportunities for reducing future relief and recovery costs and increasing fiscal stability and the long term well-being of communities in the face of increasing climate variability and flood risk under climate change. Conceptualisation and visualisation of the flood risk system, as exemplified in this paper, provides insights which might help to guide more cost-effective and sustainable flood risk mitigation investment in flood-prone communities.

Australia has the world׳s highest levels of year to year climatic variability with drought a naturally occurring component of this variability, but which may also occasionally persist for many years. Over the past 40 years climate science has provided a major contribution to improved understanding of the reasons for this high level of climatic variability with advances in seasonal forecasting research providing incentives for primary producers to adopt a more self-reliant approach to their farming operations, including drought preparedness. Over 20 major scientific publications pointed to aspects of the key climatic mechanisms – mainly associated with the El Niño phenomenon – that were now known to be responsible for drought events in Australia. Some of these publications also pointed to the means of forecasting such extreme climate events which implied the potential to prepare for drought events. Coincident enhancement of farming technologies over this period further enabled producers to create more drought resilient systems. Australian Governments have also provided many incentives to improve self-reliance and farm management and so assist preparedness for the poorer (drought) seasons and years when they occur. Government policy development over this period has been conducted with an awareness of all these factors and has therefore been able to provide changes in drought assistance through new policy endeavours that are probably unequalled in the world. This paper presents insights to the scientific, technological, and policy aspects of managing drought in Australia.

Recent reports from Japan implicated wild Sika deer (Cervus nippon) in the zoonotic transmission of hepatitis E to humans. Seroprevalence studies were performed to determine if imported feral populations of Sika deer in Maryland and Virginia posed a similar risk of transmitting hepatitis E virus (HEV). Hunters collected blood on filter paper discs from freshly killed deer. The discs were desiccated and delivered to a collection point. The dried filters were weighed to estimate the amount of blood absorbed and were eluted and collected in one tube via a novel extraction system. The procedure was quantified and validated with negative and positive serum and blood samples obtained from domestic Sika deer before and after immunization with HEV recombinant capsid protein, respectively. None of the 155 tested samples contained antibody to HEV, suggesting that Sika deer in these populations, unlike those in Japan, do not pose a significant zoonotic threat for hepatitis E. However, the new method developed for collecting and eluting the samples should prove useful for field studies of many other pathogens.

Sugarcane industries worldwide are exposed to uncertainty associated with variable climate. This variability produces impacts across an integrated value chain comprising of the following industry sectors: cane growing, harvesting and transport, milling, and marketing. The purpose of this paper is to advocate a comprehensive systems approach for using seasonal climate forecast systems to improve risk management and decision-making capability across all sugarcane industry sectors. The application of this approach is outlined for decisions relating to yield forecasting, harvest management, and the use of irrigation. Key lessons learnt from this approach include the need for a participative R&D approach with stakeholders and the need to consider the whole industry value chain. Additionally, there is the need for climate forecast systems to target the varying needs of sugarcane industries.