Spatio-Temporal Analysis of Drought Severity Using Drought Indices and Deterministic and Geostatistical Methods (Case Study: Zayandehroud River Basin)

Drought monitoring is a fundamental component of drought risk management. It is normally performed using various drought indices that are effectively continuous functions of rainfall and other hydrometeorological variables. In many instances, drought indices are used for monitoring purposes. Geostatistical methods allow the interpolation of spatially referenced data and the prediction of values for arbitrary points in the area of interest. In this research, several interpolation methods, including ordinary kriging (OK), indicator kriging (IK), residual kriging (RK), probability kriging (PK), simple kriging (SK), universal kriging (UK), and inverse distance weighted (IDW) techniques were assessed for the derivation of maps of drought indices at 19 climatic stations in Zayandehroud River Basin of Iran. Monthly rainfall data of period 1989 to 2013 were taken from 19 meteorological stations. The results showed that based on the used error criteria, kriging methods were chosen as the best method for spatial analysis of the drought indices and also, the lowest error (RMSE) and R2 is related to the kriging method. The results showed that SK and OK were more suitable for the spatial analysis of the Z-Score Index (ZSI) and the Standard Precipitation Index (SPI) index. The mean errors (RMSE) of kriging methods for ZSI and SPI indices were 0.40 and 0.19 respectively.