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Comparison of spatial interpolation methods for yield response factor of winter wheat and its spatial distribution in Haihe basin of north China

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Abstract

Yield response factor (K y) is an important basis for implementing efficient irrigation and optimal water allocation. Because K y varies in different sites, understanding its spatial distribution plays an important role in optimization irrigation in Haihe basin. After determining the K y and ET0 of winter wheat, an exponentially increasing function was found between the two parameters. Then, spherical and exponential semivariograms were chosen as proper theoretical models for ET0 and K y, respectively, with R 2 of more than 0.970. By comparing six interpolation methods as well as two procedures, i.e. ‘calculate first, interpolate later’ (CI) and ‘interpolate first, calculate later’ (IC), IC-RK (residual kriging) was considered as an optimal method in interpolating K y. Mapping of K y for winter wheat indicated an increasing trend from the western and northern mountainous region to the eastern plain region in the basin, with the K y of 0.783–1.668 for the dry growing season, 0.760–1.460 for the average growing season and 0.749–1.293 for the wet growing season. Moreover, the K y values were more than 1.0 over the most of this basin, indicating that yield loss was more important than evapotranspiration deficit, and there were greater effect of water stress on the yield of winter wheat.

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References

  • Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration. Guidelines for computing crop water requirements. United Nations Food and Agriculture Organization, Irrigation and Drainage Paper 56. Rome, Italy

  • Cambardella CA, Moorman TB, Novak JM, Parkin TB, Karlen DL, Turco RF, Konopka AE (1994) Field-scale variability of soil properties in central Iowa soils. Soil Sci Soc Am J 58:1501–1511

    Article  Google Scholar 

  • Cui YL, Li YH, Mao Z (1998) The crop-water production function with the influence of reference evapotranspiration taken into account. J Hydraul Eng 3:48–51

    Google Scholar 

  • Dağdelen N, Yılmaz E, Sezgin F, Gürbüz T (2006) Water-yield relation and water use efficiency of cotton (Gossypium hirsutum L.) and second crop corn (Zea mays L.) in western Turkey. Agric Water Manage 82(1–2):63–85

    Article  Google Scholar 

  • Dağdelen N, Başal H, Yılmaz E, Gürbüz T, Akçay S (2009) Different drip irrigation regimes affect cotton yield, water use efficiency, and fiber quality in western Turkey. Agric Water Manage 96(1):111–120

    Article  Google Scholar 

  • Dehghanisanij H, Nakhjavani MM, Tahiri AZ, Anyoji H (2009) Assessment of wheat and maize water productivities and production function for cropping system decisions in arid and semiarid regions. Irrig Drain 58(1):105–115

    Article  Google Scholar 

  • Doorenbos J, Kassam AH (1979) Yield response to water. United Nations Food and Agriculture Organization, Irrigation and Drainage Paper 33. Rome, Italy

  • ESRI (2007) ArcGIS 9.2 desktop help. Available from http://webhelp.esri.com/arcgisdesktop/9.2/index.cfm?TopicName=How_Radial_Basis_Functions_%28RBF%29_work

  • Garson GD (2009) Testing of assumptions. Available from http://faculty.chass.ncsu.edu/garson/PA765/assumpt.htm

  • Goovaerts P (1997) Geostatistics for natural resources evaluation. Oxford University Press, New York

    Google Scholar 

  • Hartkamp AD, Beurs KD, Stein A, White JW (1999) Interpolation techniques for climate variables. NRG-GIS Series 99-01. CIMMYT, Mexico, DF

  • Kipkorir EC, Raes D, Massawe B (2002) Seasonal water production functions and yield response factors for maize and onion in Perkerra, Kenya. Agric Water Manage 56(3):229–240

    Article  Google Scholar 

  • Lovelli S, Perniola M, Ferrara A, Tommaso TD (2007) Yield response factor to water (Ky) and water use efficiency of Carthamus tinctorius L. and Solanum melongena L. Agric Water Manage 92(1–2):73–80

    Article  Google Scholar 

  • Mardikis MG, Kalivas DP, Kollias VJ (2005) Comparison of interpolation methods for the prediction of reference evapotranspiration—an application in Greece. Water Resour Manage 19(3):251–278

    Article  Google Scholar 

  • Oktem A (2008) Effect of water shortage on yield, and protein and mineral compositions of drip-irrigated sweet corn in sustainable agricultural systems. Agric Water Manage 95(9):1003–1010

    Article  Google Scholar 

  • Pereira LS, Cordery I, Iacovides I (2002) Coping with water scarcity. UNESCO, IHP-VI, Technical documents in hydrology, No. 58, Paris

  • Price DT, McKenney DW, Nalder IA, Hutchinson MF, Kesteven JL (2000) A comparison of two statistical methods for spatial interpolation of Canadian monthly mean climate data. Agr For Meteorol 101(2–3):81–94

    Article  Google Scholar 

  • Rajput GS, Singh J (1986) Water production functions for wheat under different environmental conditions. Agric Water Manage 11:319–332

    Article  Google Scholar 

  • Schloeder CA, Zimmerman NE, Jacobs MJ (2001) Comparison of methods for interpolating soil properties using limited data. Soil Sci Soc Am J 65(2):470–479

    Article  CAS  Google Scholar 

  • Sezen SM, Yazar A (2006) Wheat yield response to line-source sprinkler irrigation in the arid Southeast Anatolia region of Turkey. Agric Water Manage 81(1–2):59–76

    Google Scholar 

  • Shrestha N, Geerts S, Raes D, Horemans S, Soentjens S, Maupas F, Clouet P (2010) Yield response of sugar beets to water stress under Western European conditions. Agric Water Manage 97(2):346–350

    Article  Google Scholar 

  • Tong L, Kang SZ, Zhang L (2007) Temporal and spatial variations of evapotranspiration for spring wheat in the Shiyang river basin in northwest China. Agric Water Manage 87(3):241–250

    Article  Google Scholar 

  • Yang H, Zehnder A (2001) China’s regional water scarcity and implications for grain supply and trade. Environ Plan A 33(1):79–96

    Article  Google Scholar 

  • Yazar A, Sezen SM, Sesveren S (2002) LEPA and trickle irrigation of cotton in the Southeast Anatolia Project (GAP) area in Turkey. Agric Water Manage 54(3):189–203

    Article  Google Scholar 

  • Zhang RD (2004) Applied geostatistics in environmental science. Science Press and Science Press USA Inc., NJ08852, USA

Download references

Acknowledgments

We are grateful to the research grants from the National High Technology Research and Development Program of China (2006AA100203), the National Key Basic Research Program of China (2006CB403406) and PCSIRT (IRT0657).

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Correspondence to Ling Tong.

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Communicated by A. Kassam.

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Li, X., Tong, L., Kang, S. et al. Comparison of spatial interpolation methods for yield response factor of winter wheat and its spatial distribution in Haihe basin of north China. Irrig Sci 29, 455–468 (2011). https://doi.org/10.1007/s00271-010-0251-3

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  • DOI: https://doi.org/10.1007/s00271-010-0251-3

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