Estimation method of spatial geostatistical data : Application to rainfall data

  • Authors

    • Hamid Reza Erfanian University of Science and Culture, Tehran, Iran
    • Samaneh Barati
    2017-09-16
    https://doi.org/10.14419/ijasp.v5i2.7824
  • Geostatistics, Prediction, Rainfall Data, Spatial Statistics, Universal Kriging.

  • Abstract

    Restriction of water resources for agricultural and non-agricultural purposes has caused major difficulties and rainfall is considered as one of the most important water resources. Therefore, predicting rainfall and estimating its rate monthly or annually for each region as one of the most important atmospheric parameters, is of particular importance in optimized usage of water resources.
    In this paper in addition to the presenting application of novel statistical methods, prediction of rainfall amount has been performed for the entire map of Iran. In this analysis, data of average rainfall of 108 pluviometry stations in different cities of Iran have been used and zoning of rainfall has been prepared for the country.

  • References

    1. [1] B V N P KAMBHAMMETTU, P. Allena and J. King, Application and evaluation of universal kriging for optimal contouring of groundwater levels, Journal of earth system science,vol.120,No. 3,(2011), 413-422. https://doi.org/10.1007/s12040-011-0075-4.

      [2] N. Cressie, Statistics for Spatial Data, John Wiley & Sons, New York,NY,USA,1993.

      [3] I. Hunova, J. Horalek, M. Schreiberova and M. Zapletal, Ambient Ozone exposure in Czech Forests: A GIS-based Approach to spatial distribution assessment, The Scientific Word Journal, volume 2012,(2012) .

      [4] A.G. Journel and C.J. Huijbregts, Mining Geostatistics, Academic Press, London,1978.

      [5] A. Lichtenstern, Kriging methods in spatial statistics, Bachelor's thesis, Munchen University,2013.

      [6] G. Matheron,G, Principles of geostatistics, Economic geology,vol.58,(1963),1246-1266. https://doi.org/10.2113/gsecongeo.58.8.1246.

      [7] E. Pardo-Iguzquiza and M. Chica-Olmo, Geostatistics with the Matern semivariogram model: A library of computer programs for inference, kriging and simulation, Computers & Geosciences, vol. 34,(2008), 1073–1079. https://doi.org/10.1016/j.cageo.2007.09.020.

      [8] J. Tukey, Exploratory data analysis, Addison-Wesley Publishing Company,1976.

  • Downloads

  • Received date: 2017-05-22

    Accepted date: 2017-08-07

    Published date: 2017-09-16