Zoning using climatic indices is of significant value in climate studies and climate- related planning. The aim of this study is to assess De Martonne aridity index and to select the best model to draw Iran‘s complete map based on 150 station‘s temperature and precipitation data over a 25-year period (1986-2010). Kolmogorov - Smirnov test (K–S test) was used to check the normality of the data. In order to assess De Martonne aridity index, annual temperature and precipitation data were collected from properly-distributed stations in the study period. Using De Martonne aridity index formula, this index was calculated for all the stations. In the next step, using different geostatistical methods, De Martonne aridity index map was drawn. Semivariogram was used to show the spatial correlation between aridity index data in which linear semivariograms of 0.84 was the best interpolation model to show the correlation. To estimate De Martonne aridity index, inverse distance weighting (IDW), global polynomial interpolation (GPI), radial basis function (RBF), local polynomial interpolation (LPI), as well as Kiriging methods were used. Root mean square error (RMSE), and mean absolute error (MAE) were used to select the best interpolation method. Our results showed that simple kriging method shows the highest correlation with the observed data (R2=0.77). Moreover, it is shown that Iran's central regions due to locating in low lands and being far from the northern and western mountain ranges (Alborz and Zagros) has the lowest De Martonne aridity index (< 5, 5 – 10) and is classified as arid and semi-arid areas while Iran's northern regions has the highest De Martonne aridity index (> 55) is classified as very humid area showing a wide climate range of arid to very humid in Iran.
کلید واژگان :GIS, rainfall, interpolation, temperature, semivariogram
ارزش ریالی : 600000 ریال
با پرداخت الکترونیک