The impacts of climate change on water resources and agriculture in China

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China is the world’s most populous country and a major emitter of greenhouse gases. Consequently, much research has focused on China’s influence on climate change but somewhat less has been written about the impact of climate change on China. China experienced explosive economic growth in recent decades, but with only 7% of the world’s arable land available to feed 22% of the world’s population, China's economy may be vulnerable to climate change itself. We find, however, that notwithstanding the clear warming that has occurred in China in recent decades, current understanding does not allow a clear assessment of the impact of anthropogenic climate change on China’s water resources and agriculture and therefore China’s ability to feed its people. To reach a more definitive conclusion, future work must improve regional climate simulations—especially of precipitation—and develop a better understanding of the managed and unmanaged responses of crops to changes in climate, diseases, pests and atmospheric constituents.

At a glance


  1. Distribution of vegetation across China.
    Figure 1: Distribution of vegetation across China.

    The vegetation distribution reflects present-day climate gradients. The vast area covered by agriculture and regions with different crop rotations are given in green. The red dots represent the areas with a significant (P<0.05) increase in drought expressed by the Palmer Drought Severity Index (PDSI; the higher the index the less drought) during the period 1960–2005 (see text). The green dots indicate the areas where a decrease in drought was observed. Annual PDSI at spatial resolution of 2.5° is from ref. 20. Inset, islands in area below map.

  2. Observed inter-annual variation in annual runoff in two major Chinese rivers.
    Figure 2: Observed inter-annual variation in annual runoff in two major Chinese rivers.

    a, Observed inter-annual variation in the Yangtze River annual runoff at the Datong station (red dot on China map in inset; grey shading indicates the area of the Yangtze River basin) from 1960 to 2000. The red dotted line is the fit to the Datong data: y = 2.05x3,172 (R2 = 0.05, P = 0.16). b, Observed inter-annual variation in the Yellow River annual runoff at the Lanzhou (upper basin), Huayuankou (lower basin), and Gaocun (lower basin) stations (green, blue and red dots on China map in inset; grey shading indicates the area of the Yellow River basin) from 1960 to 2000. The green dotted line is the fit to the Lanzhou data: y = −0.27x+560 (R2 = 0.19, P<0.01). The blue dotted line is the fit to the Huayuankou data: y = −0.7x+1,434 (R2 = 0.31, P<0.01). The red dotted line is the fit to the Gaocun data: y = −0.87x+1,764 (R2 = 0.44, P<0.01). The decreasing trend in Yellow River annual runoff is at least partially induced by climate change (see text). A linear regression t-test was conducted to determine whether the slope of the regression line differed significantly from zero.

  3. Observed annual rate of change in glacier area at 22 monitoring stations in western China over the past 30-40[thinsp]years.
    Figure 3: Observed annual rate of change in glacier area at 22 monitoring stations in western China over the past 30–40years.

    A negative rate indicates a shrinking glacier42, 98. Each glacier location is shown on the map inset. The photographs show examples of glacier retreat between 1985 and 2005 due to increased melting at Mount Anyemaqen, Qinghai (one of the sacred mountains in the Tibetan ethnic area of China). Top image by Matthias Kuhle; bottom image by John Vovis for Greenpeace (reproduced with permission).

  4. Observed expansion of crop pests and diseases, and changes in flooding and droughts during the period 1971-2007.
    Figure 4: Observed expansion of crop pests and diseases, and changes in flooding and droughts during the period 1971-2007.

    a, Arable land area exposed to crop pests and diseases during the period 1971–2007. The increase is partially induced by climate warming (see text). The consequences of pesticide use are shown by the red curve. The black line is a fit to the 1971–1985 data: y = 4.9x9,495 (R2 = 0.92, P<0.001). The blue line is a fit to the 1986–2007 data: y = 8.6x16,918 (R2 = 0.94, P<0.001). b, Changes in cropland areas affected by flooding and droughts, expressed as a deviation from the 1971–2007 average. The blue line is a fit to the flood data: y = 0.208x3.95 (R2 = 0.20, P = 0.006). The red line is a fit to the drought data: y = −0.030x+0.58 (R2 = 0.00, P = 0.759). c, Changes in cereal yields during the period 1971–2007, expressed as grain yield per unit area rather than total grain production because of interannual variation in the planted area. These data come from China’s agricultural statistics72, 99.

  5. The potential climate change impact on crop yield in China.
    Figure 5: The potential climate change impact on crop yield in China.

    Projected future percentage changes in the yields of rice (a), wheat (b) and maize (c) cultivated in China. The yield is defined as harvested grain biomass per unit cultivated area. Changes are expressed as the relative differences of 2020s and 2050s yields in comparison to the yield of 1996–2000. The left-hand panels show rainfed yield changes and the right-hand panels show irrigated yield changes. These results are obtained from ref. 79. In that study, the effects of CO2 fertilization and climate change are accounted for, but not the effects of future developments in agro-technology, which is assumed to remain today. The separate effects of climate and CO2 changes on yield are shown for IPCC climate scenarios A2 and B2 (ref. 7).

  6. Schematic diagram of climate change and its potential impacts on water resources and agriculture in China over the past five decades.
    Figure 6: Schematic diagram of climate change and its potential impacts on water resources and agriculture in China over the past five decades.

    Impact cycle diagrams for southeastern, western and northeastern China are superimposed on the annual precipitation map of China. Over the last few decades, China has experienced a pronounced warming. Precipitation has increased in the south and northwest of the country; in contrast, the northeastern part has suffered from drought. These changes have already produced significant impacts on agriculture as well as water resources. In western China, reducing glacier mass driven by rising temperature and increased precipitation caused an increase in runoff that benefited agriculture in western China. In northeastern China, warmer conditions and decreased rainfall have been accompanied by increased drought, which produced a negative impact on agriculture. The wetter southeastern China has had more rainfall with an increase in high rainfall events. These increased extreme rainfall events are likely to cause decreased crop yields, particularly through increased flooding. It is not clear whether the decrease in soil moisture and runoff due to the increase in evapotranspiraion (ET), driven by rising temperature, is beneficial for crop yield in southeastern China, because this region has high precipitation.

  7. Observed trends and future projections of climate in China.
    Figure 7: Observed trends and future projections of climate in China.

    a, Observed mean annual temperature variations between 1960 and 2006 across the country, expressed as deviation from the mean during that period (blue line). The blue dotted line is a fit to the data: y = 0.0263x52.13 (R2 = 0.54, P = 0.001). The inset shows trends in seasonal temperature (°C per year) during the period 1960–2006. The data come from the climate records of 412 meteorological stations. The three coloured bars on the right-hand side show the projected temperature range by 2100 for the three IPCC marker scenarios A1B, A2 and B1. Model output comes from ref. 1 and uses an ensemble of 24 models. b, As for a but for precipitation variations, but the data come from climate records at 355 meteorological stations where all daily precipitation data are available during the period of 1960–2006. The blue dotted line is a fit to the data: y = 0.0454x90.03 (R2 = 0.00, P = 0.93). c, Spatial patterns of the trend in seasonal temperature (°C per year, shown as bar graphs) from 1960 to 2006. d, Spatial patterns of the trend in seasonal precipitation (percentage per year, shown as bar graphs) from 1960 to 2006. e, Spatial patterns of the trend in frequency of summer heatwave episodes (days per decade, shown as colour scale) from 1960 to 2006. Heatwave episodes were defined as hot summer (June–August) days with temperatures exceeding the 90th percentile with respect to the reference period (1960–2006). f, Spatial patterns of the trend in rainfall days with precipitation exceeding 0mm (days per decade, shown as colour scale) from 1960 to 2006. A linear regression t-test was conducted to determine whether the slope of the regression line differed significantly from zero. Asterisks and black-edged circles indicates that the trend is statistically significant (P<0.05).


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Author information


  1. Department of Ecology, Department of Geography, College of Urban and Environmental Science, Key Laboratory for Earth Surface Processes of the Ministry of Education, and Center of Climate Research, Peking University, Beijing 100871, China

    • Shilong Piao,
    • Zehao Shen,
    • Shushi Peng,
    • Liping Zhou,
    • Hongyan Liu,
    • Yuecun Ma,
    • Kun Tan &
    • Jingyun Fang
  2. Laboratoire des Sciences du Climat et de l’Environnement, UMR CEA-CNRS-UVSQ, Batiment 709, CE L'Orme des Merisiers, Gif-sur-Yvette, F-91191, France

    • Philippe Ciais &
    • Pierre Friedlingstein
  3. State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China

    • Yao Huang,
    • Yongqiang Yu &
    • Tianyi Zhang
  4. Chinese Research Academy of Environmental Sciences, Beijing 100012, China

    • Junsheng Li
  5. Laboratory of Climate Studies, National Climate Center, China Meteorological Administration, No. 46 Zhongguancun Na Da Jie, Beijing 100081, China

    • Yihui Ding
  6. QUEST, Department of Earth Sciences, University of Bristol, Bristol, BS8 1RJ, UK

    • Pierre Friedlingstein
  7. China Water Information Center (Hydrological Bureau), Lane 2 Baiguang Road, Beijing 100053, China

    • Chunzhen Liu


Author contributions S. Piao, P.C., Y.H., Z.S., L.Z., H.L., C.L. and J.F. designed the research. S. Peng, S. Piao and K.T. performed climate change analysis. Y.H. provided agriculture data and performed related analysis. All authors contributed to the writing.

Competing financial interests

The authors declare no competing financial interests.

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  1. Report this comment #13299

    Fangyi Yang said:

    Perfect review about climate change's impact for China.

    One question relevant to the Box 1, "figure Observed trends and future projections of climate in China, f, Spatial patterns of the trend in rainfall days with precipitation exceeding 0mm", what means exceeding 0mm.

    And suggestion, For agriculture, the soil is also a critical factor, the review of the soil change under the climate change background also can help to understand the impact from climate change.

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