Impacts of climate change mitigation on agriculture water use:A provincial analysis in China

Agriculture consumes huge amounts of water in China and is profoundly affected by climate change.This study projects the agricultural water use towards 2030 under the climate change mitigation target at the provincial level in China by linking a computable general equilibrium(CGE)model and a regression model.By solving the endogeneities amongst agricultural water use,output and climate factors,we explore how these variables affect water use and further predict future trends through soft-link with the IMED|CGE model.It is found that sunshine duration has a slightly positive impact on water use.Furthermore,agricultural output will significantly drive agricultural water use based on historical data of the past 16 years.Results also show that carbon reduction would have a trade-offor co-benefit effect on water use due to regional disparity.Provinces with increasing agricultural exports,such as Xinjiang and Ningxia,would anticipate considerable growth in agricultural water use induced by carbon reduction.The soft-link method proposed by this study could be applied for future studies that aim to incorporate natural and geographical factors into human activities,and vice versa,for assessing sustainable development policies in an integrated way.

Water use efficiency data from 2000 to 2019 in measuring progress towards SDGs in Central Asia

Central Asia,located in the hinterland of the Eurasian continent,is characterized with sparse rainfall,frequent droughts and low water use efficiency.Limited water resources have become a key factor restricting the sustainable development of this region.Accurately assessing the efficiency of water resources utilization is the first step to achieve the UN Sustainable Development Goals(SDGs)in Central Asia.However,since the collapse of the Soviet Union,the evalua-tion of water use efficiency is difficult due to low data availability and poor consistency.To fill this gap,this paper developed a Water Use Efficiency dataset(WUE)based on the Moderate Resolution Imaging Spectroradiometer(MODIS)Gross Primary Production(GPP)data and the MODIS evapotranspiration(ET)data.The WUE dataset ranges from 2000 to 2019 with a spatial resolution of 500 m.The agricultural WUE was then extracted based on the Global map of irrigated areas and MODIS land use map.As a complementary,the water use amount per GDP was estimated for each country.The present dataset could reflect changes in water use efficiency of agriculture and other sectors.