Marziye Sadat Mirahsani; Abdolrasol Salman Mahini; Reza Moddares; Alireza Soffianian; Reza Jafari; Jahangir Mohhamadi
Abstract
Zayandeh Rood Basin has a vital role in Iran's poetry, biomass, agriculture, industry and tourism, faced with drought problems. Clustering approach can be a management approach to reduce drought risk impacts which groups the members with regard to the division based on the Euclidean distance of stations. ...
Read More
Zayandeh Rood Basin has a vital role in Iran's poetry, biomass, agriculture, industry and tourism, faced with drought problems. Clustering approach can be a management approach to reduce drought risk impacts which groups the members with regard to the division based on the Euclidean distance of stations. In this research, the approach of determining the spatial-temporal distribution of drought clusters in watersheds is used to express variations based on precipitation precipitation index (SPI) parameters of stations, which depends on the probability of precipitation for any time scale. Since the maximum spatial distribution of the meteorological stations in the region and the maximum time period of the long-term and possible long-term statistical period were considered the same, the data of 26 stations from 12 years (2003 to 2014) was used as reference data. In this regard, the12 months SPI index was first calculated. Then, the 12-month SPI index, which ended in December, was used for cluster analysis of the SPI, and then 144 data were clustered into four groups. Further, zoning analysis was performed on data clusters. Then, the relationship between elevations as an effective landform factor in drought with SPI drought index cluster was investigated using correlation of variables. SPI correlation with mean height of each cluster stations was studied and the results were compared and analyzed. The results of the SPI drought fluctuation chart showed a very severe drought in 2008 and 2009 and 2010, and severe drought in 2010 and mild drought in 2003, 2005 and 2013. Also, 12-month SPI drought data showed a high and negative correlation with height data. Consequently, spatial-temporal monitoring of drought indicators clusters is recommended as a way to manage the impacts of drought risk.
