Skip to main content

Advertisement

Log in

Past and future changes in regional crop water requirements in Northwest China

  • Original Paper
  • Published:
Theoretical and Applied Climatology Aims and scope Submit manuscript

Abstract

Northwest China is characterized by a high water deficit and regular water resource shortages. These issues have become limiting factors for agricultural and socioeconomic development. Based on a trend-preserving method of bias correction, we calibrated the maximum temperature and minimum temperature in four CMIP5 GCMs (CNRM, IPSL, BCC, and CMCC). Then, we investigated variations in the regional crop water requirement (CWR) in the total growth stages for five main crops (cotton, spring corn, summer corn, spring wheat, and winter wheat) in the past (1961–2005) and future (2006–2100). The results suggest that the MK test yielded insignificant decreasing CWR trends in the total growth stages of cotton (0.10 mm/year), spring corn (0.13 mm/year), and spring wheat (0.05 mm/year) and insignificant increasing trends for summer corn (0.02 mm/year) and winter wheat (0.32 mm/year) historically. In the future period, for the same type of crops (cotton), the CWRs in all scenarios (RCP 2.6, 4.5, and 8.5 scenarios) for all GCMs exhibited significant positive trends; for the same GCM (BCC), the CWRs projected for five major crops in the RCP 4.5 and 8.5 scenarios all exhibited extremely significant MK trends (99%); in addition, the CWRs’ rate increases of the five crops projected in RCP8.5 scenario by BCC exhibited the following order: winter wheat (1.25 mm/year), summer corn (1.15 mm/year), spring corn (1.02 mm/year), cotton (0.97 mm/year), and spring wheat (0.87 mm/year). The maximum CWRs of winter wheat were mainly observed in southeastern Northwest China, while those of the other four crops occurred in southern Xinjiang.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  • Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration-Guidelines for computing crop water requirements. FAO Irrigation and drainage, Rome

    Google Scholar 

  • Andrews T, Gregory JM, Webb MJ, Taylor KE (2012) Forcing, feedbacks and climate sensitivity in CMIP5 coupled atmosphere-ocean climate models. Geophys Res Lett 39(9)

  • Berg AA, Famiglietti JS, Walker JP, Houser PR (2003) Impact of bias correction to reanalysis products on simulations of North American soil moisture and hydrological fluxes. J Geophys Res Atmos 108(D16):ACL 2-1–ACL 2-15

    Article  Google Scholar 

  • Beyazgül M, Kayam Y, Engelsman F (2000) Estimation methods for crop water requirements in the Gediz Basin of western Turkey. J Hydrol 229(1):19–26

    Article  Google Scholar 

  • Cannon AJ, Sobie SR, Murdock TQ (2015) Bias correction of GCM precipitation by quantile mapping: how well do methods preserve changes in quantiles and extremes? J Clim 28(17):6938–6959

    Article  Google Scholar 

  • Chen Y, Yang Q, Luo Y (2012) Ponder on the issues of water resources in the arid region of northwest China. Arid Land Geogr 35(1):1–9

    Google Scholar 

  • Cleland EE, Chuine I, Menzel A, Mooney HA, Schwartz MD (2007) Shifting plant phenology in response to global change. Trends Ecol Evol 22(7):357–365

    Article  Google Scholar 

  • De Silva CS, Weatherhead EK, Knox JW, Rodriguez-Diaz JA (2007) Predicting the impacts of climate change—a case study of paddy irrigation water requirements in Sri Lanka. Agric Water Manag 93(1):19–29

    Article  Google Scholar 

  • Dufresne JL, Foujols MA, Denvil S, Caubel A, Marti O, Aumont O, Balkanski Y, Bekki S, Bellenger H, Benshila R (2013) Climate change projections using the IPSL-CM5 earth system model: from CMIP3 to CMIP5. Clim Dyn 40(9–10):2123–2165

    Article  Google Scholar 

  • Estrella N, Sparks TH, Menzel A (2007) Trends and temperature response in the phenology of crops in Germany. Glob Chang Biol 13(8):1737–1747

    Article  Google Scholar 

  • Fu GB, Chen S, Liu CM, Shepard D (2004) Hydro-climatic trends of the Yellow River basin for the last 50 years. Clim Chang 65(1):149–178

    Article  Google Scholar 

  • Guereña A, Ruiz-Ramos M, Díaz-Ambrona CH, Conde JR, Mínguez MI (2001) Assessment of climate change and agriculture in Spain using climate models. Agron J 93(1):237–249

    Article  Google Scholar 

  • Hagemann S, Chen C, Haerter JO, Heinke J, Gerten D, Piani C (2011) Impact of a statistical bias correction on the projected hydrological changes obtained from three GCMs and two hydrology models. J Hydrometeorol 12(4):556–578

    Article  Google Scholar 

  • Hamed KH, Rao AR (1998) A modified Mann-Kendall trend test for autocorrelated data. J Hydrol 204:182–196

    Article  Google Scholar 

  • Hao F, Zhang X, Ouyang W, Skidmore AK, Toxopeus A (2012) Vegetation NDVI linked to temperature and precipitation in the upper catchments of Yellow River. Environ Model Assess 17(4):389–398

    Article  Google Scholar 

  • Hargreaves GH, Samani ZA (1982) Estimating potential evapotranspiration. J Irr Drain Div ASCE 108(3):225–230

    Google Scholar 

  • Hempel S, Frieler K, Warszawski L, Schewe J, Piontek F (2013) A trend-preserving bias correction-the ISI-MIP approach. Earth Syst Dyn 4(2):219–236

    Article  Google Scholar 

  • Ines AV, Hansen JW (2006) Bias correction of daily GCM rainfall for crop simulation studies. Agric For Meteorol 138(1):44–53

    Article  Google Scholar 

  • Jeong SJ, Ho CH, Gim HJ, Brown ME (2011) Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982-2008. Glob Chang Biol 17(7):2385–2399

    Article  Google Scholar 

  • Kendall M (1975) Multivariate analysis. Charles Griffin Londen

  • Li S (2013) The impact of climate change on the agricultural irrigation water requirement in the Northwest arid region, China. Hebei Normal University (in Chinese)

  • Li Y, Zhou M (2014) Projections of water requirements of cotton and sugar beet in Xinjiang based on statistical downscaling model. Transactions of the Chinese Society of Agricultural Engineering 30(22):70–79 (in Chinese)

    Google Scholar 

  • Mann HB (1945) Nonparametric tests against trend. Econometrica 13:245–259

    Article  Google Scholar 

  • Matthias JT, Andreas G, Armin L (2011) Empirical-statistical downscaling and error correction of daily precipitation from regional climate models. Int J Climatol 31(10):1530–1544

    Article  Google Scholar 

  • Mehrotra R, Sharma A (2010) Development and application of a multisite rainfall stochastic downscaling framework for climate change impact assessment. Water Resour Res 46(7):759–768

    Article  Google Scholar 

  • Moonen A, Ercoli L, Mariotti M, Masoni A (2002) Climate change in Italy indicated by agrometeorological indices over 122 years. Agric For Meteorol 111(1):13–27

    Article  Google Scholar 

  • Moss RH, Edmonds JA, Hibbard KA, Manning MR, Rose SK, Van Vuuren DP, Carter TR, Emori S, Kainuma M, Kram T (2010) The next generation of scenarios for climate change research and assessment. Nature 463(7282):747–756

    Article  Google Scholar 

  • Musha R, Bai Y, Xu Q, Lei X, Liu H (2013) Impact of climate change on crop water requirement in the Tarim River Basin. Yellow River 35(3):68–70 (in Chinese)

    Google Scholar 

  • Pereira LS, Allen RG, Smith M, Raes D (2015) Crop evapotranspiration estimation with FAO56: past and future. Agric Water Manag 147:4–20

    Article  Google Scholar 

  • Sakellariou-Makrantonaki M, Vagenas I (2006) Mapping crop evapotranspiration and total crop water requirements estimation in Central Greece. European Water 13(14):3–13

    Google Scholar 

  • Sen PK (1968) Estimates of the regression coefficient based on Kendall’s tau. J Am Stat Assoc 63(324):1379–1389

    Article  Google Scholar 

  • Shen Y, Chen Y (2010) Global perspective on hydrology, water balance, and water resources management in arid basins. Hydrol Process 24(2):129–135

    Google Scholar 

  • Shen Y, Li S, Chen Y, Qi Y, Zhang S (2013) Estimation of regional irrigation water requirement and water supply risk in the arid region of Northwestern China 1989-2010. Agric Water Manag 128:55–64

    Article  Google Scholar 

  • Solomon SD, Qin M, Manning M, Marquis K, Averyt MMB, Tignor HL, Miller J, Chen E (2007) Climate change 2007: the physical science basis. Cambridge University Press, Cambridge, p 996

    Google Scholar 

  • Song XY, Li LJ, Fu GB, Li JY, Zhang AJ, Liu WB, Zhang K (2014) Spatial-temporal variations of spring drought based on spring-composite index values for the Songnen Plain, Northeast China. Theor Appl Climatol 116(3–4):371–384

    Article  Google Scholar 

  • Supit I, Van Diepen C, Boogaard H, Ludwig F, Baruth B (2010) Trend analysis of the water requirements, consumption and deficit of field crops in Europe. Agric For Meteorol 150(1):77–88

    Article  Google Scholar 

  • Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meterol Soc 93(4):485–498

    Article  Google Scholar 

  • Theil H (1950) A rank-invariant method of linear and polynomial regression analysis, I, II, III. Nederl Akad Wetensch

  • Todisco F, Vergni L (2008) Climatic changes in Central Italy and their potential effects on corn water consumption. Agric For Meteorol 148(1):1–11

    Article  Google Scholar 

  • Wan L, Zhang XP, Ma Q, Zhang JJ, Ma TY, Sun YP (2013) Spatiotemporal characteristics of precipitation and extreme events on the Loess Plateau of China between 1957 and 2009. Hydrol Process 28(18):4971–4983

    Article  Google Scholar 

  • Xin Z, Xu J, Zheng W (2008) Spatiotemporal variations of vegetation cover on the Chinese Loess Plateau (1981-2006): impacts of climate changes and human activities. Sci China Ser D 51(1):67–78 (in Chinese)

    Article  Google Scholar 

  • Xu Z, Yang ZL (2012) An improved dynamical downscaling method with GCM bias corrections and its validation with 30 years of climate simulations. J Clim 25(18):6271–6286

    Article  Google Scholar 

  • Xu C, Yang X, Li Y, Wang W (2011) Spatiotemporal change characteristics of agricultural climate resources in Northwest Arid Area. J Appl Ecol 22(3):763–772 (in Chinese)

    Google Scholar 

  • Xu L, Myneni RB, Chapin FS, Callaghan TV, Pinzon JE, Tucker CJ, Zhu Z, Bi J, Ciais P, Tømmervik H, Euskirchen ES, Forbes BC, Piao SL, Anderson BT, Ganguly S, Nemani RR, Goetz SJ, Beck PSA, Bunn AG, Cao C, Stroeve JC (2013) Temperature and vegetation seasonality diminishment over northern lands. Nat Clim Chang 3(6):581–586

    Article  Google Scholar 

  • Yue S, Pilon P, Cavadias G (2002) Power of the Mann-Kendall and Spearman’s rho tests for detecting monotonic trends in hydrological series. J Hydrol 259(1–4):254–271

    Article  Google Scholar 

  • Zamani R, Akond-Ali A, Roozbahani A, Fattahi R (2017) Risk assessment of agricultural water requirement based on a multi-model ensemble framework, southwest of Iran. Theor Appl Climatol 129(3–4):1109–1121

    Article  Google Scholar 

  • Zhang Q, Singh VP, Sun P, Chen X, Zhang Z, Li J (2011) Precipitation and streamflow changes in China: changing patterns, causes and implications. J Hydrol 410:204–216

    Article  Google Scholar 

Download references

Acknowledgements

The authors are grateful to the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP5, and we thank the climate modeling groups (CNRM-CM5, IPSL-CM5A-LR, BCC-CSM1.1, and CMCC-CM) for producing and making available their model output. Furthermore, we acknowledge the National Climate Centre of the China Meteorological Administration for their role in making the maximum temperature and minimum temperature dataset available. This research was supported by the National Key Research and Development Program of China (nos. 2016YFC0402401 and 2016YFC0501707), National Natural Science Foundation of China (nos. 41501022 and 51479171). We wish to thank the Associate Editor and the anonymous reviewers for their valuable comments and constructive suggestions, which improved the quality of the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Songbai Song or Zhi Li.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Song, X., Song, S., Li, Z. et al. Past and future changes in regional crop water requirements in Northwest China. Theor Appl Climatol 137, 2203–2215 (2019). https://doi.org/10.1007/s00704-018-2739-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00704-018-2739-3

Navigation