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

Abstract

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-off or 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.

Keywords

Climate change / Agricultural water use / Soft link / IMED|CGE / Regression model / Co-benefit / Trade-off

Acknowledgement

This study was supported by the Natural Science Foundation of China (Grant No. 51861135102; 71704005; 71810107001) and the Key Projects of National Key Research and Development Program of the Ministry of Science and Technology of China (Grant No. 2017YFC0213000). We appreciate the three anonymous reviewers and the editor for their comments that have been very helpful in improving an earlier manuscript of this paper.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi: 10.1016/j.geosus.2020.07.001.

References

[1] Adams, R., 1989. Global climate change and agriculture: An economic perspective. Am. J. Agric. Econ. 71 (5), 1272-1279.

[2] Baskerville, G., Emin, P., 1969. Rapid estimation of heat accumulation from maximum and minimum temperatures. Ecol. 50 (3), 514-517.

[3] Böhringer, C., Löschel, A., 2005. Climate policy beyond kyoto: Quo vadis? Kyklos 58 (4), 467-493.

[4] Chen, Q., 2014. Advanced Econometric and Application in Stata (Edition 2), 10, 2 ed. Higher education press, Beijing.

[5] Chen, S., Chen, X., Xu, J., 2016. Impacts of climate change on agriculture: Evidence from China. J. Environ. Econ. Manage. 76, 105-124.

[6] Chen, W., 2005. The costs of mitigating carbon emissions in China: Findings from China MARKAL-MACRO modeling. Energy Policy 33 (7), 885-896.

[7] Chen, S., Xu, J., Zhang, H., 2016. Impacts of climate change on China’s crop yield: Evidence from the county level. Chinese Rural Econ. (5) 2-15.

[8] China Meteorological Data Service Center, 2017. National meteorological observatory database. http://data.cma.cn/en/?r = site/index (accessed 20 April 2020).

[9] Dai, H., Mischke, P., Xie, X., Xie, Y., Masui, T., 2016. Closing the gap? Top-down versus bottom-up projections of China’s regional energy use and CO₂ emissions. Appl. Energy 162, 1355-1373.

[10] De Fraiture, C., Giordano, M., Liao, Y., 2008. Biofuels and implications for agricultural water use: Blue impacts of green energy. Water Policy 10 (S1), 67-81.

[11] Deschênes, O., Greenstone, M., 2007. The economic impacts of climate change: Evidence from agricultural output and random fluctuations in weather. Am. Econ. Rev. 97 (1), 354-385.

[12] Dore, M., 2005. Climate change and changes in global precipitation patterns: What do we know? Environ. Int. 31 (8), 1167-1181.

[13] Fujimori, S., Masui, T., Matsuoka, Y., 2014. Development of a global computable general equilibrium model coupled with detailed energy end-use technology. Appl. Energy 128, 296-306.

[14] Harto, C., Meyers, R., Williams, E., 2010. Life cycle water use of low-carbon transport fuels. Energy Policy 38 (9), 4933-4944.

[15] Hsiao, C., 2003. Analysis of Panel Data, 2nd Ed. Cambridge University Press, Cambridge, p. 32.

[16] Hulme, M., 2016. 1.5 °C and climate research after the Paris agreement. Nat. Clim. Chang. 6 (3), 222-224.

[17] IPCC, 2018. In: Masson-Delmotte, V., Zhai, P., Pörtner, H.-O., Roberts, D., Skea, J., Shukla, A.P.P.R., et al. (Eds.), Global Warming of 1.5 °C An IPCC Special Report On the Impacts of Global Warming of 1.5 °C Above Pre-Industrial Levels and Related Global Greenhouse Gas Emission pathways, in the Context of Strengthening the Global Response to the Threat of Climate change, Sustainable development, and Efforts to Eradicate Poverty.

[18] Li, X., Feng, K., Siu, Y., Hubacek, K., 2012. Energy-water nexus of wind power in China: The balancing act between CO₂ emissions and water consumption. Energy Policy 45, 440-448.

[19] Lin, E., Xiong, W., Ju, H., Xu, Y., Li, X., Bai, L., Xie, L., 2005. Climate change impacts on crop yield and quality with CO₂ fertilization in China. Philos. Trans. Royal Soc. B. 360 (1463), 2149-2154.

[20] Liu, X., 2018. Impacts of Agrometeorological Disasters and Temperature and Precipitation on Grain Yield in North China Plain. Master Thesis. Chinese academy of agricultural sciences, Beijing. (in Chinese)

[21] Marques, G., Lund, J., Howitt, R., 2005. Modeling irrigated agricultural production and water use decisions under water supply uncertainty. Water Resour. Res. 41 (8), W08423.

[22] Ministry of Ecology and environment, the People’s Republic of China, 2018. The People’s Republic of China Second Biennial Update Report on Climate Change. http://www.mee.gov.cn/ywgz/ydqhbh/wsqtkz/201907/P020190701765971866571.pdf (accessed 20 April 2020).

[23] Ministry of Water Resources, the People’s Republic of China, 2019. China Water Resources Bulletin 2018. http://agri.ckcest.cn/file1/M00/06/8D/Csgk0F1FYhqAIZnEAAhSt0sHE0Q105.pdf (accessed 20 April 2020).

[24] National Bureau of Statistical of China, 2020. China Statistical Database (2002-2017). http://data.stats.gov.cn/easyquery.htm?cn = E0103 (accessed 20 April 2020).

[25] National, Development and Reform, Commission,Ministry of Water Resources, 2019. National Water Conservation Plan. https://www.ndrc.gov.cn/xxgk/zcfb/ghxwj/201904/t20190418_960963.html (accessed 8 April 2020).

[26] O’Neill, B., Kriegler, E., Riahi, K., Ebi, K., Hallegatte, S., Carter, T., Mathur, R., D., 2014. A new scenario framework for climate change research: The concept of shared socioeconomic pathways. Clim. Change 122 (3), 387-400.

[27] Page, G., Ridoutt, B., Bellotti, B., 2012. Carbon and water footprint tradeoffs in fresh tomato production. J. Clean. Prod. 32, 219-226.

[28] Palatnik, R., Roson, R., 2012. Climate change and agriculture in computable general equilibrium models: Alternative modeling strategies and data needs. Clim. Chang. 112 (3), 1085-1100.

[29] Qin, D., 2018. Introduction to the Science of Climate Change. Science Press, Beijing.

[30] Ritchie, J., Nesmith, D., 1991. Temperature and crop development. In: Modeling plant and soil systems. American Society of Agronomy, Inc. Crop Science Society of America, Inc. Soil Science Society of America, Inc., Madison, pp. 5-29.

[31] Rutherford, T., 1999. Applied general equilibrium modeling with MPSGE as a GAMS subsystem: An overview of the modeling framework and syntax. Comput. Econ. 14 (1), 1-46.

[32] Schlenker, W., Roberts, M., 2009. Nonlinear temperature effects indicate severe damages to US. crop yields under climate change. Proc. Natl. Acad. Sci. USA 106 (37), 15594-15598.

[33] Siddig, K., Grethe, H., 2014. International price transmission in CGE models: How to reconcile econometric evidence and endogenous model response? Econ. Model. 38, 12-22.

[34] Su, Q., Dai, H., Lin, Y., Chen, H., Karthikeyan, R., 2018. Modeling the carbon-energy-water nexus in a rapidly urbanizing catchment: A general equilibrium assessment. J. Environ. Manage. 225, 93-103.

[35] Thornton, P., Jones, P., Alagarswamy, G., Andresen, J., 2009. Spatial variation of crop yield response to climate change in East Africa. Glob. Environ. Change 19 (1), 54-65.

[36] Tian, X., Dai, H., Geng, Y., Huang, Z., Masui, T., Fujita, T., 2017. The effects of carbon reduction on sectoral competitiveness in China: A case of Shanghai. Appl. Energy 197, 270-278.

[37] Tian, X., Geng, Y., Dai, H., Fujita, T., Wu, R., Liu, Z., Masui, T., Yang, X., 2016. The effects of household consumption pattern on regional development: A case study of Shanghai. Energy 103, 49-60.

[38] Trenberth, K., 2011. Changes in precipitation with climate change. Clim. Res. 47 (1-2), 123-138.

[39] Vörösmarty, C., Green, P., Salisbury, J., Lammers, R., 2000. Global water resources: Vulnerability from climate change and population growth. Science 289 (5477), 284-288.

[40] Wallis, P., Ward, M., Pittock, J., Hussey, K., Bamsey, H., Denis, A., Kenway, S., King, C., Mushtaq, S., Retamal, M., Spies, B., 2014. The water impacts of climate change mitigation measures. Clim. Chang. 125 (2), 209-220.

[41] Wang, K., Wang, C., Chen, J., 2009. Analysis of the economic impact of different Chinese climate policy options based on a CGE model incorporating endogenous technological change. Energy Policy 37 (8), 2930-2940.

[42] Welch, J., Vincent, J., Auffhammer, M., Moya, P., Dobermann, A., Dawe, D., 2010. Rice yields in tropical/subtropical Asia exhibit large but opposing sensitivities to minimum and maximum temperatures. Proc. National Acad. Sci. 107 (33), 14562.

[43] Yao, Y., 2016. The Spatial and Temporal Characteristics of Argo-Meteorological Disasters During 1950-2015 in China. Master Thesis. Northwest A&F University, Yangling.(in Chinese)

[44] Zhang, Y., Zhang, T., Yang, L., Sheng, L., Guo, E., Bao, N., Wu, L., 2017. Analysis on the characteristics of agricultural water use and its influencing factors in Hohhot. Environ. Develop. 29 (10), 224-226 + 230.

[45] Zhang, Z., 1998. Macroeconomic effects of CO₂ emission limits: A computable general equilibrium analysis for China. J. Policy Modeling 20 (2), 213-250.

[46] Zhou, F., Bo, Y., Ciais, P., Dumas, P., Tang, Q., Wang, X., Liu, J., Zheng, C., Polcher, J., Yin, Z., Guimberteau, M., Peng, S., Ottle, C., Zhao, X., Zhao, J., Tan, Q., Chen, L., Shen, H., Yang, H., Piao, S., Wang, H., Wada, Y., 2020. Deceleration of China’s human water use and its key drivers. Proc. National Acad. Sci. U.S.A. 117 (14), 7702-7711.