Qiang Yu

　　Northwest Agricultural and Forest University, Yangling, Shaanxi, 717200, China

　　The impacts of climate change including increase in climate variability are expected to be unequally distributed, affecting rural communities in arid regions to a greater extent due to their geographical positions, low adaptive capacities and the dependence on climate sensitive agriculture and natural resource sectors. This presentation reviews the current development in research of climate impacts on dryland agriculture in both China and Australia, which includes the following aspects.

　　1）Climate impacts on crop yields over past decades

　　Historical crop yield data at regional level from 1889 in Australia were used to diagnose the impacts of historical climate change/variability on wheat growth and yield over the past century. Wheat yield, water-use and their relationship with climate change/variability will be assessed.

　　2）Modelling future climate change impacts on crop production

　　Future climate change data sets with scenarios of greenhouse gas (GHG) emissions at the site-scale were used to analyse future climate impacts impacts. The approach adopted in this project is: (a) to downscale the future climate data under future scenarios generated by GCMs, and then to analyse the future climate changes; and, (b) to predict the response of wheat growth, water use and GHG emissions using crop model.

　　3）Vulnerability and adaptation skills

　　A conceptual framework was proposed to analyse the vulnerability to climate variability over 244 rural counties of the Loess Plateau. Measures of exposure, sensitivity and adaptive capacity were combined into a vulnerability index, which integrates socio-economic data, meteorological data, natural resources and environment condition to conduct a county-level quantitative assessment. At last the regional vulnerability was mapped. Agronomic adaptation skills to climate change including change in sowing dates, plastic film mulching, irrigation scheduling, and change in fertiliser application were discussed.

　　There will be challenges and uncertainties for agriculture in future. Geo-information science, big data and crop modelling techniques, will provide support for more sustainable and efficient farming practices.