Skip to main content
SpringerLink
Log in

Mapping Monthly Precipitation in New Zealand by Using Different Interpolation Methods

  • Conference paper
  • First Online:
New Metropolitan Perspectives (NMP 2020)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 178))

Included in the following conference series:

  • 80 Accesses

Abstract

Spatial interpolation of rainfall data is an issue particularly significant for hydrological modelling and watershed management. The success of spatial interpolation varies according to the type of model chosen, its mode of geographical management and the resolution used. The aim of this paper was to develop different algorithms of spatial interpolation of rainfall in New Zealand and to compare the results of geostatistical and deterministic approaches in order to choose the method that best reproduces the actual surface. In particular, inverse distance weighting, ordinary kriging, kriging with an external drift and ordinary cokriging were applied to produce the monthly rainfall maps of New Zealand. The prediction performance of each method was evaluated through cross-validation and visual examination of the precipitation maps produced. Results clearly indicate that geostatistical methods outperform inverse distance. Moreover, among these methods, the ordinary cokriging and the kriging with an external drift showed the smallest error of prediction.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Free shipping worldwide - see info
Hardcover Book
USD 279.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Buttafuoco, G., Caloiero, T., Guagliardi, I., Ricca, N.: Drought assessment using the reconnaissance drought index (RDI) in a southern Italy region. In: 6th IMEKO TC19 Symposium on Environmental Instrumentation and Measurements, pp. 52–55 (2016a)

    Google Scholar 

  2. Frazier, A.G., Giambelluca, T.W., Diaz, H.F., Needham, H.L.: Comparison of geostatistical approaches to spatially interpolate month-year rainfall for the Hawaiian Islands. Int. J. Climatol. 36, 1459–1470 (2016)

    Article  Google Scholar 

  3. Gaglioti, S., Infusino, E., Caloiero, T., Callegari, G., Guagliardi, I.: Geochemical characterization of spring waters in the Crati River Basin, Calabria (Southern Italy). Geofluids 2019, Article ID 3850148 (2019)

    Google Scholar 

  4. Ly, S., Charles, C., Degré, A.: Geostatistical interpolation of daily rainfall at catchment scale: the use of several variogram models in the Ourthe and Ambleve catchments. Belgium. Hydrol. Earth Syst. Sci. 15, 2259–2274 (2011)

    Article  Google Scholar 

  5. Ricca, N., Guagliardi, I.: Multi-temporal dynamics of land use patterns in a Site of Community Importance in southern Italy. App. Ecol. Environ. Res. 13, 677–691 (2015)

    Google Scholar 

  6. Delbari, M., Afrasiab, P., Jahani, S.: Spatial interpolation of monthly and annual rainfall in northeast of Iran. Meteorol. Atmos. Phys. 122, 103–113 (2013)

    Article  Google Scholar 

  7. Mirás-Avalos, J.M., Paz-González, A., E. Vidal-Vázquez, E., Sande-Fouz, P.: Mapping monthly rainfall data in Galicia (NW Spain) using inverse distances and geostatistical methods. Adv. Geosci. 10, 51–57 (2007)

    Google Scholar 

  8. Goovaerts, P.: Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. J. Hydrol. 228, 113–129 (2000)

    Article  Google Scholar 

  9. Modica, G., Pollino, M., Lanucara, S., La Porta, L., Pellicone, G., Di Fazio, S., Fichera, C.R.: Land suitability evaluation for agro-forestry: definition of a web-based Multi-Criteria Spatial Decision Support System (MC-SDSS): preliminary results. In: Gervasi, O., Murgante, B., Misra, S., Rocha, A.M.A.C., Torre, C., Taniar, D., Apduhan, B.O., Stankova, E., Wang, S. (eds.) ICCSA 2016. LNCS, vol. 9788, pp. 399–413. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-42111-7_31

    Chapter  Google Scholar 

  10. Legates, D.R., Willmott, C.J.: Mean seasonal and spatial variability in global surface air temperature. Theor. App. Climat. 41, 11–21 (1990)

    Article  Google Scholar 

  11. Hutchinson, M.F., Gessler, P.E.: Splines – more than just a smooth interpolator. Geoderma 62, 45–67 (1994)

    Article  Google Scholar 

  12. Agnew, M.D., Palutikof, J.P.: GIS-based construction of baseline climatologies for the Mediterranean using terrain variables. Clim. Res. 14, 115–127 (2000)

    Article  Google Scholar 

  13. Vicente-Serrano, S.M., Saz-Sánchez, M.A., Cuadrat, J.M.: Comparative analysis of interpolation methods in the middle Ebro Valley (Spain): application to annual precipitation and temperature. Clim. Res. 24, 161–180 (2003)

    Article  Google Scholar 

  14. Goovaerts, P.: Geostatistics for Natural Resources Evaluation, 483 pp. Oxford University Press, New York (1997)

    Google Scholar 

  15. Isaaks, E.H., Srivastava, R.M.: An Introduction to Applied Geostatistics. Oxford University Press, Oxford (1989)

    Google Scholar 

  16. Moral, F.J.: Comparison of different geostatistical approaches to map climate variables: application to precipitation. Int. J. Climatol. 30, 620–631 (2010)

    Article  Google Scholar 

  17. Pellicone, G., Caloiero, T., Modica, G., Guagliardi, I.: Application of several spatial interpolation techniques to monthly rainfall data in the Calabria region (southern Italy). Int. J. Climatol. 38, 3651–3666 (2018)

    Article  Google Scholar 

  18. Pellicone, G., Caloiero, T., Guagliardi, I.: The De Martonne aridity index in Calabria. J. Map. 15, 788–796 (2019)

    Article  Google Scholar 

  19. Tsintikidis, D., Georgakakos, K.P., Sperfslage, J.A., Smith, D.E., Carpenter, T.M.: Precipitation uncertainty, raingauge network design within Folsom Lake watershed. J. Hydrol. Eng. 7, 175–184 (2002)

    Article  Google Scholar 

  20. Xu, W., Zou, Y., Zhang, G., Linderman, M.: A comparison among spatial interpolation techniques for daily rainfall data in Sichuan Province. China. Int. J. Climatol. 35, 2898–2907 (2015)

    Article  Google Scholar 

  21. Dirks, K.N., Hay, J.E., Stow, C.D., Harris, D.: High-resolution studies of rainfall on Norfolk Island, Part II: interpolation of rainfall data. J. Hydr. 208, 187–193 (1998)

    Article  Google Scholar 

  22. Dravitzki, S., McGregor, J.: Extreme precipitation of the Waikato region. New Zealand. Int. J. Climatol. 31, 1803–1812 (2011)

    Article  Google Scholar 

  23. Garnier, B.: New Zealand Weather and Climate. Whitcombe and Tombs Ltd., Christchurch (1950)

    Google Scholar 

  24. Oliver, J.E.: Encyclopedia of World Climatology. Springer, Netherlands (2005)

    Book  Google Scholar 

  25. Tomlinson, A.I.: Climate. In: Ward, I. (ed.) New Zealand Atlas, Government Printer, Wellington, pp. 82–89 (1976)

    Google Scholar 

  26. Sinclair, M.R.: An objective cyclone climatology for the Southern Hemisphere. Mon. Weather Rev. 122, 2239–2256 (1994)

    Article  Google Scholar 

  27. Sinclair, M.R.: A climatology of cyclogenesis for the Southern Hemisphere. Mon. Weather Rev. 123, 1601–1619 (1995)

    Article  Google Scholar 

  28. Sinclair, M.R.: An extended climatology of extratropical cyclones over the Southern Hemisphere. Weather Clim. 15, 21–32 (1995)

    Article  Google Scholar 

  29. Trenberth, K.E.: Storm tracks in the Southern Hemisphere. J. Atmos. Sci. 48, 2159–2178 (1991)

    Article  Google Scholar 

  30. NIWA: Overview of New Zealand Climate (2003). http://www.niwa.co.nz/education-and-training/schools/resources/climate/overview

  31. Caloiero, T.: Analysis of rainfall trend in New Zealand. Environ. Earth Sci. 73(10), 6297–6310 (2014). https://doi.org/10.1007/s12665-014-3852-y

    Article  Google Scholar 

  32. Caloiero, T.: Drought analysis in New Zealand using the standardized precipitation index. Environ. Earth Sci. 76(16), 1–13 (2017). https://doi.org/10.1007/s12665-017-6909-x

    Article  Google Scholar 

  33. Caloiero, T.: Trend of monthly temperature and daily extreme temperature during 1951–2012 in New Zealand. Theoret. Appl. Climatol. 16, 111–127 (2016). https://doi.org/10.1007/s00704-016-1764-3

    Article  Google Scholar 

  34. Caloiero, T.: SPI trend analysis of New Zealand applying the ITA technique. Geosciences 8, 101 (2018)

    Article  Google Scholar 

  35. Caloiero, T.: Evaluation of rainfall trends in the South Island of New Zealand through the innovative trend analysis (ITA). Theoret. Appl. Climatol. 139, 493–504 (2019). https://doi.org/10.1007/s00704-019-02988-5

    Article  Google Scholar 

  36. Pebesma, E., Graeler, B.: Package “gstat.” CRAN Reference Manual (2016). https://cran.r-project.org/web/packages/gstat/index.html

  37. Lu, G.Y., Wong, D.W.: An adaptive inverse-distance weighting spatial interpolation technique. Comput. Geosci. 34, 1044–1055 (2008)

    Article  Google Scholar 

  38. Webster, R., Oliver, M.A.: Geostatistics for Environmental Scientists, 2nd edn., 315 pp. Wiley, West Sussex (2007)

    Google Scholar 

  39. Chiles, J., Delfiner, P.: Geostatistics: Modeling Spatial Uncertainty. Wiley, New York (1999)

    Book  Google Scholar 

  40. Cressie, N.A.: Geostatistical analysis of spatial data. In: Spatial Statistics and Digital Image Analysis, pp. 87–108. National Academy Press Washington, D.C. (1991)

    Google Scholar 

  41. Buttafuoco, G., Guagliardi, I., Tarvainen, T., Jarva, J.: A multivariate approach to study the geochemistry of urban topsoil in the city of Tampere. Finland. J. Geochem. Exp. 181, 191–204 (2017)

    Article  Google Scholar 

  42. Buttafuoco, G., Tarvainen, T., Jarva, J., Guagliardi, I.: Spatial variability and trigger values of arsenic in the surface urban soils of the cities of Tampere and Lahti. Finland. Environ. Earth Sci. (2016). https://doi.org/10.1007/s12665-016-5707-1

    Article  Google Scholar 

  43. Buttafuoco, G., Caloiero, T., Ricca, N., Guagliardi, I.: Assessment of drought and its uncertainty in a southern Italy area (Calabria region). Measurement 113, 205–210 (2018)

    Article  Google Scholar 

  44. Guagliardi, I., Rovella, N., Apollaro, C., Bloise, A., De Rosa, R., Scarciglia, F., Buttafuoco, G.: Modelling seasonal variations of natural radioactivity in soils: a case study in southern Italy. J. Earth Syst. Sci. 125, 1569–1578 (2016)

    Article  Google Scholar 

  45. Lloyd, C.D.: Assessing the effect of integrating elevation data into the estimation of monthly precipitation in Great Britain. J. Hydrol. 308, 128–150 (2005)

    Article  Google Scholar 

  46. Kyriakidis, P.C., Kim, J., Miller, N.L.: Geostatistical mapping of precipitation from rain gauge data using atmospheric and terrain characteristics. J. Appl. Meteorol. 40, 1855–1877 (2001)

    Article  Google Scholar 

  47. Moges, S.A., Alemaw, B.F., Chaoka, T.R., Kachroo, R.K.: Rainfall interpolation using a remote sensing CCD data in a tropical basin – a GIS and geostatistical application. Phys. Chem. Earth 32, 976–983 (2007)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute for Agricultural and Forest Systems in the Mediterranean (CNR-ISAFOM), National Research Council of Italy, Via Cavour 4/6, 87036, Rende, CS, Italy

    Gaetano Pellicone, Tommaso Caloiero & Ilaria Guagliardi

Authors
  1. Gaetano Pellicone
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tommaso Caloiero
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ilaria Guagliardi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ilaria Guagliardi .

Editor information

Editors and Affiliations

  1. Mediterranea University of Reggio Calabria, Reggio Calabria, Reggio Calabria, Italy

    Carmelina Bevilacqua

  2. Mediterranea University of Reggio Calabria, Reggio Calabria, Reggio Calabria, Italy

    Francesco Calabrò

  3. Mediterranea University of Reggio Calabria, Reggio Calabria, Reggio Calabria, Italy

    Lucia Della Spina

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Pellicone, G., Caloiero, T., Guagliardi, I. (2021). Mapping Monthly Precipitation in New Zealand by Using Different Interpolation Methods. In: Bevilacqua, C., Calabrò, F., Della Spina, L. (eds) New Metropolitan Perspectives. NMP 2020. Smart Innovation, Systems and Technologies, vol 178. Springer, Cham. https://doi.org/10.1007/978-3-030-48279-4_153

Download citation

Publish with us

Policies and ethics

Search

Navigation