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\hypersetup{pdftitle={Comparing Deterministic and Geostatistics Methods in Providing of Soil Physical and Chemical Characteristics Maps},pdfauthor={Maryam Saffariha, Vahid Habibi},pdfsubject={Tropentag 2010: Abstract},pdfkeywords={Cokriging, Geostatistical methods, Kriging, spatial variability},pdfpagemode=None,colorlinks=true}
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\parbox[b]{13.4cm}{\centering \large{\textbf{Tropentag, September 14-16, 2010, Zurich}}\\[1ex] \Large{``World Food System  ---\\A Contribution from Europe''\\[2ex]}}
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\begin{center}
\Large{\textbf{Comparing Deterministic and Geostatistics Methods in Providing of Soil Physical and Chemical Characteristics Maps\footnote{\textbf{Contact Address:} Maryam Saffariha, University of Tehran, Department of Range and Watershed Management, Beheshti Stdaryaye Noor St9th Avenue40 Plaque, 0098~Tehran, Iran, \mbox{e-mail}: \email{m_snowlight@yahoo.com}}\\[0.8ex]}}
\normalsize{\textsc{Maryam Saffariha$^{1}$, Vahid Habibi$^{2}$}}
\end{center}
\begin{itemize*}
\item[]{\small{\textit{$^{1}$University of Tehran, Department of Range and Watershed Management, Iran}}}
\item[]{\small{\textit{$^{2}$University of Tehran, Department of Range and Watershed Management, }}}
\end{itemize*}
\index[author]{Saffariha, Maryam}
\index[author]{Habibi, Vahid}
\begin{center}
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\textbf{Abstract}
\begin{abstract}
\normalsize{
Understanding of soil chemical and physical characteristics and their spatial variability is necessary to range management. In our study, we modeled spatial variability of chemical and physical characteristics including Na, Ca , K , Mg ,EC ,SP \% , Silt , Clay and Sand in the Masilleh Plain, Qom .



We compared Deterministic and Geostatistics methods spatial variability using (radial function, inverse distance weight, local estimation, Ordinary Kriging, Disjunctive Kriging and Cokriging) methods. At first, normality of data tested by using Kolmogorov---Smirnov test, then we transformed Ca, K, Mg, and EC and silt data using logarithmic transformation. Variographic and cross variogram of data calculated. We interpreted result of estimated and expected amount using MAE and MBE.



In statistics, the mean absolute error is a quantity used to measure how close forecasts or predictions are to the eventual outcomes. In the normal state these indexes mast be zero. Positive or negative values indicated the higher and lower contents of actual estimation. Result showed:



1) There is intermediate spatial structure in Ca and \% sand parameters and other parameters have weak spatial structure



 2) Examine correlation between parameters showed that K, Mg, Ca variables high rather correlation with auxiliary variables and other parameters



3) Result showed significance of Geostatistical methods in comparison to deterministic methods.



 4)Cokriging is the best method for modelling of Ca and EC, Disjunctive Kriging is the suitable methods for modelling of SP \%, Mg, Na, Silt and Clay. On the other hand ordinary Kriging is the best method for modelling of K and Sand.



}

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\noindent \textbf{Keywords:} Cokriging, Geostatistical methods, Kriging, spatial variability
\index[key]{Cokriging}
\index[key]{Geostatistical methods}
\index[key]{Kriging}
\index[key]{Spatial!variability}
\end{document}