Drought Monitoring Using Climatic Indices and Geostatistic Technique (Case Study: Hossein Abad Plain, Sarbisheh, Iran)
محورهای موضوعی : Journal of Water Sciences Research
H Ghasemi
1
(M. Sc. Graduate of Combating Desertification, Birjand, Iran)
A.A Gholami
2
(M. Sc. of Water instruction, Islamic Azad University, Ferdows, Iran)
GH.R Hadarbadi
3
(PHD Student of Environmental Management, Department of Environmental and Energy, Science and Research Branch, Islamic Azad
University, Tehran, Iran)
H Ebrahimi
4
(Assistant Professor, Islamic Azad University, Ferdows, Iran)
کلید واژه: Drought Monitoring, Climatic indices, Geostatistical methods,
چکیده مقاله :
Of the many climatic events that influence the Earth’s environment, drought is perhaps the one that is most linked with desertification. Drought is the consequence of a natural reduction in the amount of precipitation received over an extended period, usually a season or more in length. Drought monitoring is an essential component of drought risk management. It is normally performed using various drought indices that are effectively continuous functions of rainfall and other climatic variables. A number of drought indices have been introduced and applied in different countries to date. This paper compares the performance of two indices for drought monitoring in Hossein Abad Plain which includes several catchments and villages. The indices used include deciles and standard precipitation indexes. The comparison of indices is based on drought cases and classes that were detected in the12 synoptic stations over the 11 years of data, as well as over the latest 1998–2001 drought spell. Then by using ArcGIS 9.2 software were planned drought and wetness maps. The method of interpolate was Kriging (one of suitable Geo statistical methods).The results show that SPI respond slowly to drought onset. DI appears to be very responsive to rainfall events of a particular year, but it has inconsistent spatial and temporal variation. The SPI was found to be able to detect the onset of drought, its spatial and temporal variation consistently, and it may be recommended for operational drought monitoring in the country and SPI was found to be more responsive to the emerging drought and performed better.
