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Abstract Regional crop production forecasting is growing in importance in both, the public and private sectors to ensure food security, optimize agricultural management practices and use of resources, and anticipate market fluctuations. Thus, a model and data driven, easy-to-use forecasting and a risk assessment system can be an essential tool for end-users at different levels. This paper provides an overview of the approaches, algorithms, design, and capabilities of the CCAFS Regional Agricultural Forecasting Toolbox (CRAFT) for gridded crop modeling and yield forecasting along with risk analysis and climate impact studies. CRAFT is a flexible and adaptable software platform designed with a user-friendly interface to produce multiple simulation scenarios, maps, and interactive visualizations using a crop engine that can run the pre-installed crop models DSSAT, APSIM, and SARRA-H, in concert with the Climate Predictability Tool (CPT) for seasonal climate forecasts. Its integrated and modular design allows for easy adaptation of the system to different regional and scientific domains. CRAFT requires gridded input data to run the crop simulations on spatial scales of 5 and 30 arc-minutes. Case studies for South Asia for two crops, including wheat and rice, shows its potential application for risk assessment and in-season yield forecasting. Highlights • An integrated modeling framework, CRAFT, has been developed for gridded simulations at 5 and 30 arc-minutes resolutions. • It allows within-season yield forecasting, risk analysis, and climate change impact studies. • It incorporates seasonal climate forecasts using the Climate Predictability Tool. • The current version can run the pre-installed DSSAT, APSIM, and SARRA-H, but support for any crop model can be added. • CRAFT is a desktop application that can produce multiple simulation scenarios, maps, and interactive visualizations. [ABSTRACT FROM AUTHOR]

This paper provides an ex-ante assessment of the impacts of climate and price variability on household income and food security in Ethiopia and Ghana. The study applies an agent-based modelling approach to highlight the role of coping and adaptation strategies under climate and price variability. Our simulation results show that climate and price variability adversely affects income and food security of households in both countries. Self-coping mechanisms are found to be important but insufficient to mitigate the adverse effects of variability, implying the need for policy interventions. Adaptation strategies composed of a portfolio of actions such as the provision of production credit and access to improved seeds are found to be effective in reducing the impacts of climate and price variability in Ethiopia. Similarly, policy interventions aimed at improving the provision of short-term production credit along with the existing irrigation facilities are important in Ghana. Finally, this study highlights the importance of capturing the distributional aspects of adaptation options by highlighting heterogeneous effects of variability and adaptation options. [ABSTRACT FROM AUTHOR]

Abstract: Significant progress has been made in the use of ensemble agricultural and climate modelling, and observed data, to project future productivity and to develop adaptation options. An increasing number of agricultural models are designed specifically for use with climate ensembles, and improved methods to quantify uncertainty in both climate and agriculture have been developed. Whilst crop–climate relationships are still the most common agricultural study of this sort, on-farm management, hydrology, pests, diseases and livestock are now also examined. This paper introduces all of these areas of progress, with more detail being found in the subsequent papers in the special issue. Remaining scientific challenges are discussed, and a distinction is developed between projection- and utility-based approaches to agro-climate ensemble modelling. Recommendations are made regarding the manner in which uncertainty is analysed and reported, and the way in which models and data are used to make inferences regarding the future. A key underlying principle is the use of models as tools from which information is extracted, rather than as competing attempts to represent reality. [Copyright &y& Elsevier]

Forty seven percent of the population of Pakistan is food insecure, access to food is uneven and malnutrition is widespread. In addition, food production depends greatly on irrigation, including the use of substantial volumes of water from already stressed aquifers. Our aim in this paper is to examine the implications of continued population growth on the required production of food and the implied water demand. We examine the historical trends of crop production, water use, food availability and population growth in Pakistan, and project them forward to 2050. Food availability has improved over recent decades, mostly as a result of increasing the area and water use of crops and fodder, and partly as a result of importing more pulses and cooking oils. We show that a continuation of current trends leads to nearly a doubling of the (already unsustainable) groundwater use. There is uncertainty in the magnitude of climate change impacts, but climate change may further exacerbate matters. To avoid further increases of groundwater use, some combination would be required of: more dams and other irrigation infrastructure; increasing crop yields (particularly yields per unit volume of water) at a greater rate than in the past; a change in crop mix away from high water use crops like rice and sugarcane, to crops that use less water; and, exporting less and importing more food. The alternatives appear difficult to implement quickly, so it appears likely that in the short to medium term more groundwater will be consumed, with attendant problems of water quality and sustainability. Our analysis provides new perspectives on past trends and future food and water (including groundwater) challenges. [ABSTRACT FROM AUTHOR]

Growing demands for food security to feed increasing populations worldwide have intensified the search for improved performance of irrigation, the world’s largest water user. These challenges are raised in the face of climate variability and from growing environmental demands. Adaptation measures in irrigated agriculture include fallowing land, shifting cropping patterns, increased groundwater pumping, reservoir storage capacity expansion, and increased production of risk-averse crops. Water users in the Gila Basin headwaters of the U.S. Lower Colorado Basin have faced a long history of high water supply fluctuations producing low-valued defensive cropping patterns. To date, little research grade analysis has investigated economically viable measures for irrigation development to adjust to variable climate. This gap has made it hard to inform water resource policy decisions on workable measures to adapt to climate in the world’s dry rural areas. This paper’s contribution is to illustrate, formulate, develop, and apply a new methodology to examine the economic performance from irrigation capacity improvements in the Gila Basin of the American Southwest. An integrated empirical optimization model using mathematical programming is developed to forecast cropping patterns and farm income under two scenarios (1) status quo without added storage capacity and (2) with added storage capacity in which existing barriers to development of higher valued crops are dissolved. We find that storage capacity development can lead to a higher valued portfolio of irrigation production systems as well as more sustained and higher valued farm livelihoods. Results show that compared to scenario (1), scenario (2) increases regional farm income by 30%, in which some sub regions secure income gains exceeding 900% compared to base levels. Additional storage is most economically productive when institutional and technical constraints facing irrigated agriculture are dissolved. Along with additional storage, removal of constraints on weak transportation capacity, limited production scale, poor information access, weak risk-bearing capacity, limited management skills, scarce labor supply, low food processing capacity, and absolute scale constraints, all can raise the economic value of additional irrigation capacity development. Our results light a path forward to policy makers, water administrators, and farm managers, who bear the burden of protecting farm income, food and water security, and rural economic development in the world’s dry regions faced by the need to adapt to climate variability. [ABSTRACT FROM AUTHOR]

Climate change is expected to affect both the amount of global crop production, and annual variability in food supply. Agriculture is a major source of greenhouse gas emissions, but also considered to mitigate climate change. Conservation tillage, as a climate-smart agricultural practice, is repeatedly reported to mitigate net greenhouse gas emissions by increasing soil organic carbon (SOC). However, with reduced tillage, less litter is moved from the surface deeper into the soil profile, so SOC increase is very likely constrained to topsoil layers. Further adaptation benefits, such as increasing crop yield and resilience to famine, have recently been questioned after averaging yields from field studies. However, such global averaging masks the geographic extent individual studies apply to. This paper attempts a holistic regional analysis on the benefits of conservation tillage, in particular its fundamental principle no-tillage (NT), on the Chinese Loess Plateau. Based on a review of almost 20 years of conservation tillage plot experiments, the potential of NT to increase SOC stocks and to adapt to lower but more variable rainfall in the future has been assessed. The results show that the difference of total SOC stocks between NT and CT decreased with soil depth, confirming that the SOC benefits of NT are concentrated to the immediate topsoil still subject to direct seeding. The topsoil achieved maximum SOC stocks after about 10 years of NT. Crop yields from NT increased by up to 20% for years with average and below average precipitation, demonstrating the advantages of NT in stabilizing crop yields in dry years. However, the results in previous reports are not weighted by the actual spatial extent of drylands and humid regions after counting individual plot studies. As a consequence of such global and unweighted averaging, the benefits from NT to increase SOC stocks are likely to misrepresent the actual impact. Therefore, given the size of the Loess Plateau and its relevance for food security in China, our analysis illustrates the need to assess the benefits of a tillage and residue management system for each combination of eco-region and farming practice, weighted by their area and the affected population, rather than just using a global average for policy development on sustainable productivity. [ABSTRACT FROM AUTHOR]

The potentially devastating impacts of climate change on crop production and food security are now widely acknowledged. An important component of efforts to mitigate these impacts is the production of new varieties of crops which will be able to thrive in more extreme and changeable environmental conditions. There is therefore an urgent need to find new sources of genetic diversity for crop improvement. Wild plant species closely related to crops (crop wild relatives) contain vital sources of such genes, yet these resources themselves are threatened by the effects of climate change, as well as by a range of other human-induced pressures and socio-economic changes. The flora of China comprises more than 20,000 native higher plant species, a proportion of which have known or potential value as gene donors for crop improvement. However, until now, the full range of these valuable crop wild relative species had not been identified. In this paper we present a methodology for creating a checklist of, and prioritizing China’s crop wild relatives, and reveal that 871 native species are related to crops that are of particularly high socio-economic importance in China—including rice, wheat, soybean, potato, sweet potato, millet and yam—crops which are also of notably high value for food and economic security in other parts of the world. Within this list we have identified species that are in particular need of conservation assessment based on their relative Red List status and potential for use in crop improvement programs. Endemic species that have particularly high economic value potential in China and that are under severe threat of genetic erosion and thus in need of urgent conservation action include wild relatives of tea ( Camellia fangchengensis S. Yun Liang et Y.C. Zhong and C. grandibracteata H.T. Chang et F.L. Yu), apple ( e.g ., Malus honanensis Rehder, M. ombrophila Hand.-Mazz. and M. toringoides (Rehder) Hughes), and pear ( Pyrus pseudopashia T.T. Yu). We provide recommendations for developing a systematic and comprehensive national CWR conservation strategy for China, highlighting the challenges and requirements of taking the strategy forward to the implementation phase. [ABSTRACT FROM AUTHOR]

During the past decade, the application of agricultural production systems modelling has rapidly expanded while there has been less emphasis on model improvement. Cropping systems modelling has become agricultural modelling, incorporating new capabilities enabling analyses in the domains of greenhouse gas emissions, soil carbon changes, ecosystem services, environmental performance, food security, pests and disease losses, livestock and pasture production, and climate change mitigation and adaptation. New science has been added to the models to support this broadening application domain, and new consortia of modellers have been formed that span the multiple disciplines. There has not, however, been a significant and sustained focus on software platforms to increase efficiency in agricultural production systems research in the interaction between the software industry and the agricultural modelling community. This paper describes the changing agricultural modelling landscape since 2002, largely from a software perspective, and makes a case for a focussed effort on the software implementations of the major models. [ABSTRACT FROM AUTHOR]

Abstract: The purpose of this paper is to identify which of the world''s cereal producing regions are likely to become vulnerable to climate change over the 21st century by identifying those regions that will be (1) exposed to climatic stress and (2) have a limited capacity to adapt. First, we use a global hydrological model to identify regions likely to be exposed to drought, defined here as a location where the available soil moisture is projected to decline by the 2050s and 2080s relative to the mean soil moisture observed between 1990 and 2005. Second, we use agricultural, meteorological and socio-economic data to develop models of adaptive capacity and run these models to show where adaptive capacity is likely to decline by the 2050s and 2080s relative to the baseline period of 1990–2005. Third, we contrast the hydrological and adaptive capacity model outputs to identify “vulnerability hotspots” for wheat and maize. Here, a vulnerability hotspot is defined as a region that the models project as likely to experience both a decline in adaptive capacity and in available soil moisture. Results from the hydrological model project significant drying in many parts of the world overt the 21st century. Results from the adaptive capacity models show that regions with the lowest overall adaptive capacity for wheat include much of western Russia, northern India, southeastern South America, and southeastern Africa. In terms of maize, regions with the lowest adaptive capacity include the northeastern USA, southeastern South America, southeastern Africa, and central/northern India. When taken together, this study identifies five wheat and three maize growing regions likely to be both exposed to worse droughts and a reduced capacity to adapt. For wheat, these are: southeastern USA, southeastern South America, the northeastern Mediterranean, and parts of central Asia. For maize, our analysis suggests that vulnerability hotspots are: southeastern South America, parts of southern Africa, and the northeastern Mediterranean. [Copyright &y& Elsevier]

Abstract: China is one of the most important rice production countries in the world, and maintaining high rice productivity in China is very important for world food security. While previous studies showed that rice production in China has been and will be negatively impacted by global warming, the confounding effects of climatic change, variety improvement and agronomic managements have not been separately investigated. In this paper we combine an analysis of climate and rice growth data with crop modeling to investigate the impact of changes in climate, rice varieties, and agronomic management on rice productivity at four sites (Wuchang, Xinyang, Zhenjiang and Hanyuan) in China. The results showed a significant increase in minimum temperature during all rice growth stages at Wuchang and Zhenjiang, and from heading to maturity at Xinyang, but little change at Hanyuan. Global warming would have led to a reduction in the length of rice growing period and a reduction in grain yield at all study sites, if no varietal changes had occurred. However, the adoption of new rice varieties stabilized growing duration, increased harvest index and grain yield at three of the four sites. In the face of future warming, a planned breeding effort may be needed to offset the negative impact of future climate change. [Copyright &y& Elsevier]

Abstract: This article gives a brief review of the development and current situation in global irrigation, and looks at the drivers affecting irrigation performance, development and modernization. The article concludes that the options for new developments are limited, and that future investment will need to be more precisely targeted to specific niches in different agroecological and economic contexts. The paper notes the powerful implications of global climatic change on irrigation through changes in hydrology and water supply that, in conjunction with (1) continued demand for cheap food to satisfy continuously growing populations and changing dietary preferences (projected to 2050) and (2) increasing competition for high reliability water from higher value economic sectors, indicate irrigation performance and the productivity of agricultural water use must further improve, and are also likely to become more targeted at higher value enterprises. Improving management, through better institutions and better technology will require constant adaptation and finessing, with no silver bullets currently on the horizon. [Copyright &y& Elsevier]

The impact of climate change on agricultural systems has become a reality that currently threatens food security in numerous regions worldwide. However, concrete consequences of climate change on agricultural yields still remain unknown in many countries around the world, including Romania. This study conducts a first-ever analysis of the impact of climate change on maize productivity in Romania, the European Union's leader in maize harvested production, which holds almost 30% of the European maize production. The paper explores complex statistical relationships between the climatic water balance (CWB)/its constituting parameters precipitation (P) and reference evapotranspiration (ETo) and maize yields (Zea mays L.) recorded nationally from 1990 to 2013, a key-period in Romania in terms of climate and socio-political changes. The analysis of various agro-climatic data, based on well-established methods (linear regression and bootstrapping), showed that the countrywide dependence of maize yields variability to changes in the analyzed climatic variables was considerable and reached peak values of roughly 60% for the CWB-yield relationship and around 50% for the P-yield and ETo-yield relationships. At the same time, a significant sensitivity of maize yield dynamics was found in response to a 1-unit climate change, which, on average, was quantified at 5 kg/ha/yr for a 1-mm variation of the CWB, and at 19 kg/ha/yr and 11 kg/ha/yr for a 1-mm change in P and ETo, respectively. In addition to this agricultural impact, our findings regarding the economic impact associated to concrete climatic trends (CWB decreases and ETo increases over the 24 years, consistent with an overall increase of the humidity deficit, and P increases, consistent with humidity surplus) indicate total costs of approximately 53 mil € (or almost 1% of the national agricultural gross domestic product) for the CWB-yield relationship, and of ~200 mil € (~3%) for ETo-yield. It was found that the separate influence of P in maize dynamics was positive, with net financial gains of up to ~130 mil € (~2%). However, our findings show that only the economic costs associated with the impact of ETo on maize productivity are highly statistically reliable. Our results issue a warning about the urgent measures to fight climate change effects on agriculture in Romania, which are necessary especially in the counties located in the Extra-Carpathian regions, highly vulnerable to climate dynamics. • Investigation of climate change impact on agricultural yields in Romania after 1990. • Analysis between climatic water balance (CWB)/precipitation (P)/reference evapotranspiration (ETo) and maize yields. • Up to ~60% dependence of maize yields variability to climatic changes, for the CWB – maize yields relationship. • Average sensitivity of 5 kg/ha/yr, 19 kg/ha/yr and 11 kg/ha/yr, for a 1-mm variation of the CWB, P and ETo. • Total economic costs of up to 53 mil €/200 mil €, associated with the negative impact of CWB/ETo on maize yields. [ABSTRACT FROM AUTHOR]