Deep Learning for Improved Agricultural Risk Management

Deep learning provides many benefits, including automation, speed, accuracy, and intelligence, and it is delivering competitive performance now across a wide range of real-world operational applications - from credit card fraud detection to recommender systems and customer segmentation. Its potential in actuarial sciences and agricultural insurance/risk management, however, remains largely untapped. In this pilot study, we investigate deep learning in predicting agricultural yield in time and space under weather/climate uncertainty. We evaluate the predictive power of deep learning, benchmarking its performance against more conventional approaches alongside both weather station and climate. Our findings reveal that deep learning offers the highest predictive accuracy, outperforming all the other approaches. We infer that it also has great potential to reduce underwriting inefficiencies and insurance coverage costs associated with using more imprecise yield-based metrics of real risk exposure. Future work aims to further evaluate its performance, from municipal area-yield, to finer-scale crop-specific producer-scale yield

Scaling Success: Lessons from Adaptation Pilots in the Rainfed Regions of India

"Scaling Success" examines how agricultural communities are adapting to the challenges posed by climate change through the lens of India's rainfed agriculture regions. Rainfed agriculture currently occupies 58 percent of India's cultivated land and accounts for up to 40 percent of its total food production. However, these regions face potential production losses of more than $200 billion USD in rice, wheat, and maize by 2050 due to the effects of climate change. Unless action is taken soon at a large scale, farmers will see sharp decreases in revenue and yields.Rainfed regions across the globe have been an important focus for the first generation of adaptation projects, but to date, few have achieved a scale that can be truly transformational. Drawing on lessons learnt from 21 case studies of rainfed agriculture interventions, the report provides guidance on how to design, fund and support adaptation projects that can achieve scale

Technologies for climate change adaptation: agricultural sector

This Guidebook presents a selection of technologies for climate change adaptation in the agricultural sector. A set of twenty two adaptation technologies are showcased that are primarily based on the principals of agroecology, but also include scientific technologies of climate and biological sciences complemented with important sociological and institutional capacity building processes that are required to make adaptation function. The technologies cover monitoring and forecasting the climate, sustainable water use and management, soil management, sustainable crop management, seed conservation, sustainable forest management and sustainable livestock management. Technologies that tend to homogenize the natural environment and agricultural production have low possibilities of success in conditions of environmental stress that are likely to result from climate change. On the other hand, technologies that allow for, and indeed promote, diversity are more likely to provide a strategy which strengthens agricultural production in the face of uncertain future climate change scenarios. In this sense, the twenty two technologies showcased in this Guidebook have been selected because they facilitate the conservation and restoration of diversity while at the same time providing opportunities for increasing agricultural productivity. Many of these technologies are not new to agricultural production practices, but they are implemented based on assessment of current and possible future impacts of climate change in a particular location. Agro-ecology is an approach that encompasses concepts of sustainable production and biodiversity promotion and therefore provides a useful framework for identifying and selecting appropriate adaptation technologies for the agricultural sector. The Guidebook provides a systematic analysis of the most relevant information available on climate change adaptation technologies in the agriculture sector. It has been compiled based on a literature review of key publications, journal articles, and e-platforms, and by drawing on documented experiences sourced from a range of organizations working on projects and programmes concerned with climate change adaptation technologies in the agricultural sector. Its geographic scope is focused on developing countries where high levels of poverty, agricultural production, climate variability and biological diversity currently intersect. Key concepts around climate change adaptation are not universally agreed. It is therefore important to understand local contexts – especially social and cultural norms - when working with national and sub-national stakeholders to make informed decisions about appropriate technology options. Thus, decision-making processes should be participative, facilitated, and consensus-building oriented and should be based on the following key guiding principles: increasing awareness and knowledge, strengthening institutions, protecting natural resources, providing financial assistance and developing context-specific strategies. For decision-making the Community–Based Adaptation framework is proposed for creating inclusive governance that engages a range of stakeholders directly with local or district government and national coordinating bodies, and facilitates participatory planning, monitoring and implementation of adaptation activities. Seven criteria are suggested for the prioritization of adaptation technologies: (i) The extent to which the technology maintains or strengthens biological diversity and is environmentally sustainable; (ii) The extent to which the technology facilitates access to information systems and awareness of climate change information; (iii) Whether the technology support water, carbon and nutrient cycles and enables stable and/or increased productivity; (iv) Income-generating potential, cost-benefit analysis and contribution to improved equity; (v) Respect for cultural diversity and facilitation of inter-cultural exchange; (vi) Potential for integration into regional and national policies and can be scaled-up; (vii) The extent to which the technology builds formal and information institutions and social networks. Finally, recommendations are set out for practitioners and policy makers: • There is an urgent need for improved climate modelling and forecasting which can provide a basis for informed decision-making and the implementation of adaptation strategies. This should include traditional knowledge. • Information is also required to better understand the behaviour of plants, animals, pests and diseases as they react to climate change. • Potential changes in economic and social systems in the future under different climate scenarios should also be investigated so that the implications of adaptation strategy and planning choices are better understood. • It is important to secure effective flows of information through appropriate dissemination channels. This is vital for building adaptive capacity and decision-making processes. • Improved analysis of adaptation technologies is required to show how they can contribute to building adaptive capacity and resilience in the agricultural sector. This information needs to be compiled and disseminated for a range of stakeholders from local to national level. • Relationships between policy makers, researchers and communities should be built so that technologies and planning processes are developed in partnership, responding to producers’ needs and integrating their knowledge

Identifying Advantages and Disadvantages of Variable Rate Irrigation – An Updated Review

Variable rate irrigation (VRI) sprinklers on mechanical move irrigation systems (center pivot or lateral move) have been commercially available since 2004. Although the number of VRI, zone or individual sprinkler, systems adopted to date is lower than expected there is a continued interest to harness this technology, especially when climate variability, regulatory nutrient management, water conservation policies, and declining water for agriculture compound the challenges involved for irrigated crop production. This article reviews the potential advantages and potential disadvantages of VRI technology for moving sprinklers, provides updated examples on such aspects, suggests a protocol for designing and implementing VRI technology and reports on the recent advancements. The advantages of VRI technology are demonstrated in the areas of agronomic improvement, greater economic returns, environmental protection and risk management, while the main drawbacks to VRI technology include the complexity to successfully implement the technology and the lack of evidence that it assures better performance in net profit or water savings. Although advances have been made in VRI technologies, its penetration into the market will continue to depend on tangible and perceived benefits by producers

Climate change, agriculture and Fairtrade: identifying the challenges and opportunities

This paper presents the findings of a study commissioned by the UK's Fairtrade Foundation on the implications of climate change for agricultural producers in Fairtrade value chains

Towards an\u2028 EU research and innovation policy agenda for nature-based solutions & re-naturing cities. Final report of the Horizon 2020 expert group on nature-based solutions and re-naturing cities.

1. Nature-based solutions harness the power and sophistication of nature to turn environmental, social and economic challenges into innovation opportunities. They can address a variety of societal challenges in sustainable ways, with the potential to contribute to green growth, 'future-proofing' society, fostering citizen well-being, providing business opportunities and positioning Europe as a leader in world markets. \u2028 2. Nature-based solutions are actions which are inspired by, supported by or copied from nature. They have tremendous potential to be energy and resource-efficient and resilient to change, but to be successful they must be adapted to local conditions. \u2028 3. Many nature-based solutions result in multiple co-benefits for health, the economy, society and the environment, and thus they can represent more efficient and cost-effective solutions than more traditional approaches. \u2028 4. An EU Research & Innovation (R&I) agenda on nature-based solutions will enable Europe to become a world leader both in R&I and in the growing market for nature-based solutions. For this, the evidence base for the effectiveness of nature-based solutions needs to be developed and then used to implement solutions. Both need to be done in conjunction with stakeholders. The potential for transferability and upscaling of solutions also requires further investigation. There is also a need to develop a systemic approach that combines technical, business, finance, governance, regulatory and social innovation. \u2028 5. Four principal goals have been identified that can be addressed by nature-based solutions: �� Enhancing sustainable urbanisation through nature-based solutions can stimulate economic growth as well as improving the environment, making cities more attractive, and enhancing human well-being. \u2028 �� Restoring degraded ecosystems using nature-based solutions can improve the resilience of ecosystems, enabling them to deliver vital ecosystem services and also to meet other societal challenges. \u2028 �� Developing climate change adaptation and mitigation using nature-based solutions can provide more resilient responses and enhance the storage of carbon. \u2028 �� Improving risk management and resilience using nature-based solutions can lead to greater benefits than conventional methods and offer synergies in reducing multiple risks. \u2028 6. Based on the four goals, seven nature-based solutions for R&I actions are recommended to be taken forward by the European Commission and Member States: �� Urban regeneration through nature-based solutions \u2028 �� Nature-based solutions for improving well-being in urban areas \u2028 �� Establishing nature-based solutions for coastal resilience \u2028 �� Multi-functional nature-based watershed management and ecosystem restoration \u2028 �� Nature-based solutions for increasing the sustainability of the use of matter and energy \u2028 �� Nature-based solutions for enhancing the insurance value of ecosystems \u2028 �� Increasing carbon sequestration through nature-based solutions \u2028This report was produced by the Horizon 2020 Expert Group on 'Nature-Based Solutions and Re- Naturing Cities', informed by the findings of an e-consultation and a stakeholder workshop. \u202

The Digitalisation of African Agriculture Report 2018-2019

An inclusive, digitally-enabled agricultural transformation could help achieve meaningful livelihood improvements for Africa’s smallholder farmers and pastoralists. It could drive greater engagement in agriculture from women and youth and create employment opportunities along the value chain. At CTA we staked a claim on this power of digitalisation to more systematically transform agriculture early on. Digitalisation, focusing on not individual ICTs but the application of these technologies to entire value chains, is a theme that cuts across all of our work. In youth entrepreneurship, we are fostering a new breed of young ICT ‘agripreneurs’. In climate-smart agriculture multiple projects provide information that can help towards building resilience for smallholder farmers. And in women empowerment we are supporting digital platforms to drive greater inclusion for women entrepreneurs in agricultural value chains

Tracing sources of cadmium in agricultural soils: a stable isotope approach

Cadmium (Cd) is a biotoxic heavy metal, which is accumulated by plants and animals and thereby enters the human food chain (Gray et al. 2003). The application of phosphate fertilisers has also resulted in the long-term accumulation of Cd in agricultural soils around the world, including New Zealand (NZ). In 1997, the main source of NZ phosphate fertilisers was changed from Nauru island phosphate rocks (450 mg Cd kg-1 P) to a variety of phosphate rocks with lower Cd concentrations, in order to meet more stringent Cd limits in P fertiliser. Following this change, the accumulation of Cd in topsoil samples from the Winchmore research farm (South Island, NZ) was evaluated and was found to have plateaued post-2000 (McDowell, 2012). In this study, stable isotope analysis was used to trace the fate of Cd in Winchmore farm soils in order to determine the cause of the plateau. The isotope ratio of Cd (δ114/110Cd) was measured in pre-2000 and post-2000 phosphate fertilisers, phosphate rocks, topsoil (0-7.5 cm) and control (unfertilised) subsoil (25-30 cm) samples from the Winchmore site. The analysed topsoil samples were archived samples collected over the period 1959-2015. The isotopic compositions of fertilised topsoils ranged from δ114/110Cd = 0.08 ± 0.03 to δ114/110Cd = 0.27 ± 0.04, which were comparable to pre-2000 fertilisers (δ114/110Cd = 0.10 ± 0.05 to 0.25 ± 0.04) but distinct from the post-2000 fertilisers (δ114/110Cd range of -0.17 ± 0.03 to 0.01 ± 0.05) and control subsoil (δ114/110Cd = -0.33 ± 0.04) (Salmanzadeh et al., 2017). We combined this stable isotope data with Bayesian modelling to estimate the contribution of different sources of Cd. An open source Bayesian isotope mixing model implemented in Matlab (Arendt et al., 2015) was used here with some modifications to estimate the fractional contribution of different sources of Cd through time including pre- and post-2000 fertilisers, and the control soil. The Matlab code of Arendt et al., 2015 was modified to consider only one isotope system (rather than two), and fewer sources. This modelling confirmed the dominant contribution (about 80%) of Nauru-derived (i.e. pre-2000) fertilisers in increasing the Cd concentration in Winchmore soils. To help constrain the soil Cd mass balance we used an existing model (CadBal) (Roberts and Longhurst, 2005), to estimate residual soil Cd and output fluxes based on known P fertiliser application rates, the initial Cd concentration, farm and soil type, and soil dry bulk density. We incorporated the isotope data into the mass balance expression in order to evaluate the performance of CadBal in estimating the past topsoil Cd accumulation and predicting the future concentrations and isotope ratios of Cd (up to 2030 AD). The results of mass balance modelling confirm that recent applications of phosphate fertilisers have not resulted in an accumulation of Cd during the most recent period, thus Cd removal by either leaching or crop uptake has increased, which is consistent with the modelled isotope data (Figure 1). We can conclude that it becomes possible to distinguish the sources of Cd within the soil using stable Cd isotopes (Imseng et al., 2018) and that the residual Cd in topsoil at Winchmore still mainly originates from historical phosphate fertilisers (Salmanzadeh et al., 2017). One implication of this finding is that the contemporary applications of phosphate fertiliser are not resulting in further Cd accumulation. We aim to continue our research into Cd fate, mobility, and transformations in the NZ environment by applying Cd isotopes in soils and aquatic environments across the country. Figure 1. Results of Cd mass balance modelling in CadBal for the period of topsoil fertilisation including a prediction up to the year 2030 AD. (a) Mean concentration of Cd in the dryland treatment of Winchmore long-term irrigation trial (symbols) and the CadBal model (lines) outputs (red symbols = this study- plot 15 of Winchmore site; grey symbols = McDowell study-average of all plots; solid black line = dryland optimized CadBal from McDowell (2012) for all irrigation plots; black dashed line = Plot 15 dryland optimized CadBal-this study, first scenario; blue line = Plot 15 dryland optimized CadBal-this study, second scenario; red line = Plot 15 dryland optimized CadBal-this study, third scenario; red dashed line = Plot 15 dryland optimized CadBal-this study, fourth scenario); (b) Measured and modelled Cd isotope ratios based on CadBal outputs, isotope ratios measured in fertilisers and the fractionation factors of Wiggenhauser, et al. (2016); lines designate modelling scenarios as in (a), red dots are the third scenario with no fractionation (α factor not applied); (c) modeled scenario 3 (solid) and scenario 4 (dashed) isotope ratios in topsoil (red lines), leachate (blue lines) and pasture (green lines)