Increasing dominance of Indian Ocean variability impacts Australian wheat yields.

The relationships between crop productivity and climate variability drivers are often assumed to be stationary over time. However, this may not be true in a warming climate. Here we use a crop model and a machine learning algorithm to demonstrate the changing impacts of climate drivers on wheat productivity in Australia. We find that, from the end of the nineteenth century to the 1980s, wheat productivity was mainly subject to the impacts of the El Niño Southern Oscillation. Since the 1990s, the impacts from the El Niño Southern Oscillation have been decreasing, but those from the Indian Ocean Dipole have been increasing. The warming climate has brought more occurrences of positive Indian Ocean Dipole events, resulting in severe yield reductions in recent decades. Our findings highlight the need to adapt seasonal forecasting to the changing impacts of climate variability to inform the management of climate-induced yield losses.

Sources of uncertainty for wheat yield projections under future climate are site-specific.

Understanding sources of uncertainty in climate-crop modelling is critical for informing adaptation strategies for cropping systems. An understanding of the major sources of uncertainty in yield change is needed to develop strategies to reduce the total uncertainty. Here, we simulated rain-fed wheat cropping at four representative locations in China and Australia using eight crop models, 32 global climate models (GCMs) and two climate downscaling methods, to investigate sources of uncertainty in yield response to climate change. We partitioned the total uncertainty into sources caused by GCMs, crop models, climate scenarios and the interactions between these three. Generally, the contributions to uncertainty were broadly similar in the two downscaling methods. The dominant source of uncertainty is GCMs in Australia, whereas in China it is crop models. This difference is largely due to uncertainty in GCM-projected future rainfall change across locations. Our findings highlight the site-specific sources of uncertainty, which should be one step towards understanding uncertainties for more robust climate-crop modelling.

High-resolution climate projections for South Asia to inform climate impacts and adaptation studies in the Ganges-Brahmaputra-Meghna and Mahanadi deltas.

Climate impacts and adaptation studies often use output from impact models that require data representing future climates at a resolution greater than can be provided by Global Climate Models (GCMs). This paper describes the use of Regional Climate Model (RCM) simulations to generate high-resolution future climate information for assessing climate impacts in the Ganges-Brahmaputra-Meghna (GBM) and Mahanadi deltas as part of the DECCMA project. In this study, three different GCMs (HadGEM2-ES, CNRM-CM5 and GFDL-CM3), all using a single scenario for future greenhouse forcing of the atmosphere (RCP 8.5), were downscaled to a horizontal resolution of 25 km over south Asia using the HadRM3P RCM. These three GCMs were selected based on ability to represent key climate processes over south Asia and ability to sample a range of regional climate change responses to greenhouse gas forcing. RCM simulations of temperature, precipitation, and lower level (850 hPa) atmospheric circulation in the monsoon season (June, July, August, September - JJAS) were compared with observational datasets and their respective driving GCMs to ensure large-scale consistency. Although there are some biases in the RCM simulations, these comparisons indicate that the RCMs are able to simulate realistically aspects of the observed climate of South Asia, such as the monsoon circulation and associated precipitation that are key for informing downstream impacts and adaptation studies. Simulated future temperature and precipitation changes on seasonal and daily timescales suggest increases in both temperature and precipitation across all three models during the monsoon season, with an increase in the amount of extremely heavy precipitation over the GBM and Mahanadi basins. Despite different driving conditions, these results are consistent across all three RCM simulations, providing a level of confidence in the magnitudes and spatial characteristics of temperature and precipitation projections for South Asia.

Modelling impacts of climate change and socio-economic change on the Ganga, Brahmaputra, Meghna, Hooghly and Mahanadi river systems in India and Bangladesh.

The Ganga-Brahmaputra-Meghna (GBM) River System, the associated Hooghly River and the Mahanadi River System represent the largest river basins in the world serving a population of over 780 million. The rivers are of vital concern to India and Bangladesh as they provide fresh water for people, agriculture, industry, conservation and support the Delta System in the Bay of Bengal. Future changes in both climate and socio-economics have been investigated to assess whether these will alter river flows and water quality. Climate datasets downscaled from three different Global Climate Models have been used to drive a daily process based flow and water quality model. The results suggest that due to climate change the flows will increase in the monsoon period and also be enhanced in the dry season. However, once socio-economic changes are also considered, increased population, irrigation, water use and industrial development reduce water availability in drought conditions, threatening water supplies and posing a threat to river and coastal ecosystems. This study, as part of the DECCMA (Deltas, vulnerability and Climate Change: Migration and Adaptation) project, also addresses water quality issues, particularly nutrients (N and P) and their transport along the rivers and discharge into the Delta System. Climate will alter flows, increasing flood flows and changing pollution dilution factors in the rivers, as well as other key processes controlling water quality. Socio-economic change will affect water quality, as water diversion strategies, increased population and industrial development alter the water balance and enhance fluxes of nutrients from agriculture, urban centers and atmospheric deposition.

Modeling future flows of the Volta River system: Impacts of climate change and socio-economic changes.

As the scientific consensus concerning global climate change has increased in recent decades, research on potential impacts of climate change on water resources has been given high importance. However in Sub-Saharan Africa, few studies have fully evaluated the potential implications of climate change to their water resource systems. The Volta River is one of the major rivers in Africa covering six riparian countries (mainly Ghana and Burkina Faso). It is a principal water source for approximately 24 million people in the region. The catchment is primarily agricultural providing food supplies to rural areas, demonstrating the classic water, food, energy nexus. In this study an Integrated Catchment Model (INCA) was applied to the whole Volta River system to simulate flow in the rivers and at the outlet of the artificial Lake Volta. High-resolution climate scenarios downscaled from three different Global Climate Models (CNRM-CM5, HadGEM2-ES and CanESM2), have been used to drive the INCA model and to assess changes in flow by 2050s and 2090s under the high climate forcing scenario RCP8.5. Results show that peak flows during the monsoon months could increase into the future. The duration of high flow could become longer compared to the recent condition. In addition, we considered three different socio-economic scenarios. As an example, under the combined impact from climate change from downscaling CNRM-CM5 and medium+ (high economic growth) socio-economic changes, the extreme high flows (Q5) of the Black Volta River are projected to increase 11% and 36% at 2050s and 2090s, respectively. Lake Volta outflow would increase +1% and +5% at 2050s and 2090s, respectively, under the same scenario. The effects of changing socio-economic conditions on flow are minor compared to the climate change impact. These results will provide valuable information assisting future water resource development and adaptive strategies in the Volta Basin.

Simulating climate change and socio-economic change impacts on flows and water quality in the Mahanadi River system, India.

Delta systems formed by the deposition of sediments at the mouths of large catchments are vulnerable to sea level rise and other climate change impacts. Deltas often have some of the highest population densities in the world and the Mahanadi Delta in India is one of these, with a population of 39 million. The Mahanadi River is a major river in East Central India and flows through Chattisgarh and Orissa states before discharging into the Bay of Bengal. This study uses an Integrated Catchment Model (INCA) to simulate flow dynamics and water quality (nitrogen and phosphorus) and to analyze the impacts of climate change and socio-economic drivers in the Mahanadi River system. Future flows affected by large population growth, effluent discharge increases and changes in irrigation water demand from changing land uses are assessed under shared socio-economic pathways (SSPs). Model results indicate a significant increase in monsoon flows under the future climates at 2050s (2041-2060) and 2090s (2079-2098) which greatly enhances flood potential. The water availability under low flow conditions will be worsened because of increased water demand from population growth and increased irrigation in the future. Decreased concentrations of nitrogen and phosphorus are expected due to increased flow hence dilution. Socio-economic scenarios have a significant impact on water quality but less impact on the river flow. For example, higher population growth, increased sewage treatment discharges, land use change and enhanced atmospheric deposition would result in the deterioration of water quality, while the upgrade of the sewage treatment works lead to improved water quality. In summary, socio-economic scenarios would change future water quality of the Mahanadi River and alter nutrient fluxes transported into the delta region. This study has serious implications for people's livelihoods in the deltaic area and could impact coastal and Bay of Bengal water ecology.

Applying the global RCP-SSP-SPA scenario framework at sub-national scale: A multi-scale and participatory scenario approach.

To better anticipate potential impacts of climate change, diverse information about the future is required, including climate, society and economy, and adaptation and mitigation. To address this need, a global RCP (Representative Concentration Pathways), SSP (Shared Socio-economic Pathways), and SPA (Shared climate Policy Assumptions) (RCP-SSP-SPA) scenario framework has been developed by the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC-AR5). Application of this full global framework at sub-national scales introduces two key challenges: added complexity in capturing the multiple dimensions of change, and issues of scale. Perhaps for this reason, there are few such applications of this new framework. Here, we present an integrated multi-scale hybrid scenario approach that combines both expert-based and participatory methods. The framework has been developed and applied within the DECCMA1 project with the purpose of exploring migration and adaptation in three deltas across West Africa and South Asia: (i) the Volta delta (Ghana), (ii) the Mahanadi delta (India), and (iii) the Ganges-Brahmaputra-Meghna (GBM) delta (Bangladesh/India). Using a climate scenario that encompasses a wide range of impacts (RCP8.5) combined with three SSP-based socio-economic scenarios (SSP2, SSP3, SSP5), we generate highly divergent and challenging scenario contexts across multiple scales against which robustness of the human and natural systems within the deltas are tested. In addition, we consider four distinct adaptation policy trajectories: Minimum intervention, Economic capacity expansion, System efficiency enhancement, and System restructuring, which describe alternative future bundles of adaptation actions/measures under different socio-economic trajectories. The paper highlights the importance of multi-scale (combined top-down and bottom-up) and participatory (joint expert-stakeholder) scenario methods for addressing uncertainty in adaptation decision-making. The framework facilitates improved integrated assessments of the potential impacts and plausible adaptation policy choices (including migration) under uncertain future changing conditions. The concept, methods, and processes presented are transferable to other sub-national socio-ecological settings with multi-scale challenges.

Australian wheat production expected to decrease by the late 21st century.

Climate change threatens global wheat production and food security, including the wheat industry in Australia. Many studies have examined the impacts of changes in local climate on wheat yield per hectare, but there has been no assessment of changes in land area available for production due to changing climate. It is also unclear how total wheat production would change under future climate when autonomous adaptation options are adopted. We applied species distribution models to investigate future changes in areas climatically suitable for growing wheat in Australia. A crop model was used to assess wheat yield per hectare in these areas. Our results show that there is an overall tendency for a decrease in the areas suitable for growing wheat and a decline in the yield of the northeast Australian wheat belt. This results in reduced national wheat production although future climate change may benefit South Australia and Victoria. These projected outcomes infer that similar wheat-growing regions of the globe might also experience decreases in wheat production. Some cropping adaptation measures increase wheat yield per hectare and provide significant mitigation of the negative effects of climate change on national wheat production by 2041-2060. However, any positive effects will be insufficient to prevent a likely decline in production under a high CO2 emission scenario by 2081-2100 due to increasing losses in suitable wheat-growing areas. Therefore, additional adaptation strategies along with investment in wheat production are needed to maintain Australian agricultural production and enhance global food security. This scenario analysis provides a foundation towards understanding changes in Australia's wheat cropping systems, which will assist in developing adaptation strategies to mitigate climate change impacts on global wheat production.