چکیده:
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 geostatistical 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) methods were assessed for the derivation of maps of drought indices at 12 climatic stations in southern Iran. Data regarding monthly rainfall, temperature, wind, relative humidity, and sunshine of three periods (1985, 1995, and 2005) were taken from 12 meteorological synoptic stations and distributed areas. Based on the used error criteria, kriging methods were used for spatial analysis of the drought indexes and were selected as the best method. Results also
showed that the lowest error (RMSE) is related to the kriging method. The results indicated that IK with tree frequency is more appropriate for the spatial analysis of the RDI index, and the Pk and SK methods are more appropriate for the spatial analysis of the SPI index. The kriging methods mean errors (RMSE) selected years for RDI and SPI index respectively are 0.85 and 0.84. In several cases, the “moderately dry” class received a more critical value by RDI. The results showed that by utilizing the ET0, the RDI can be very sensitive to climatic variability.
خلاصه ماشینی:
ir DESERT 18 (2013) 79-87 Assessment of Severity of Droughts Using Geostatistics Method (Case Study: Southern Iran) A.
In this research, several geostatistical 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) methods were assessed for the derivation of maps of drought indices at 12 climatic stations in southern Iran.
Based on the used error criteria, kriging methods were used for spatial analysis of the drought indexes and were selected as the best method.
The kriging methods mean errors (RMSE) selected years for RDI and SPI index respectively are 0.
Keywords: Drought; RDI; SPI; Geostatistics Method; South of Iran 1.
In this study, kriging (K) and inverse distance weighted (IDW) geostatistical methods were assessed to identify the optimum method for SPI and RDI indices.
With survey amounts and drought intensity estimated through RDI and SPI, the best zoning and spread drought by assist ones of geostatistics methods with minor errors accomplished for during three periods time 1985, 1995, and 2005.
As seen in this table, for SPI and RDI indices, the lowest error (RMSE) was related to the kriging method.
Based on the used error criteria, kriging methods were used for spatial analysis of the drought indices and were selected as the best methods.
Kriging method mean errors (RMSE) for the selected years for RDI and SPI index are 0.
Comparability Analyses of the SPI and RDI Meteorological Drought Indices in Different Climatic Zones.