Arid
DOI10.1007/s40333-020-0095-5
Prediction of meteorological drought in arid and semi-arid regions using PDSI and SDSM: a case study in Fars Province, Iran
Dehghan, Sheida1; Salehnia, Nasrin2; Sayari, Nasrin1; Bakhtiari, Bahram1
Corresponding AuthorSayari, Nasrin
JournalJOURNAL OF ARID LAND
ISSN1674-6767
EISSN2194-7783
Year Published2020
Volume12Issue:2Pages:318-330
Abstract in English

Drought is one of the most significant environmental disasters, especially in arid and semi-arid regions. Drought indices as a tool for management practices seeking to deal with the drought phenomenon are widely used around the world. One of these indicators is the Palmer drought severity index (PDSI), which is used in many parts of the world to assess the drought situation and continuation. In this study, the drought state of Fars Province in Iran was evaluated by using the PDSI over 1995-2014 according to meteorological data from six weather stations in the province. A statistical downscaling model (SDSM) was used to apply the output results of the general circulation model in Fars Province. To implement data processing and prediction of climate data, a statistical period 1995-2014 was considered as the monitoring period, and a statistical period 2019-2048 was for the prediction period. The results revealed that there is a good agreement between the simulated precipitation (R-2>0.63; R-2, determination coefficient; MAE<0.52; MAE, mean absolute error; RMSE<0.56; RMSE, Root Mean Squared Error) and temperature (R-2>0.95, MAE<1.74, and RMSE<1.78) with the observed data from the stations. The results of the drought monitoring model presented that dry periods would increase over the next three decades as compared to the historical data. The studies showed the highest drought in the meteorological stations Abadeh and Lar during the prediction period under two future scenarios representative concentration pathways (RCP4.5 and RCP8.5). According to the results of the validation periods and efficiency criteria, we suggest that the SDSM is a proper tool for predicting drought in arid and semi-arid regions.


Keyword in EnglishPDSI SDSM RCP4 5 RCP8 5 climate change extreme drought
SubtypeArticle
Language英语
CountryIran
Indexed BySCI-E
WOS IDWOS:000531437700011
WOS KeywordSEVERITY INDEX ; CLIMATE-CHANGE ; PRECIPITATION ; TEMPERATURE ; BASIN ; CHINA
WOS SubjectEnvironmental Sciences
WOS Research AreaEnvironmental Sciences & Ecology
Document Type期刊论文
Identifierhttp://119.78.100.177/qdio/handle/2XILL650/318510
Affiliation1.Shahid Bahonar Univ Kerman, Dept Water Engn, Fac Agr, Kerman 7616914111, Iran;
2.Ferdowsi Univ Mashhad, Fac Agr, Mashhad 9177949207, Razavi Khorasan, Iran
Recommended Citation
GB/T 7714
Dehghan, Sheida,Salehnia, Nasrin,Sayari, Nasrin,et al. Prediction of meteorological drought in arid and semi-arid regions using PDSI and SDSM: a case study in Fars Province, Iran[J],2020,12(2):318-330.
APA Dehghan, Sheida,Salehnia, Nasrin,Sayari, Nasrin,&Bakhtiari, Bahram.(2020).Prediction of meteorological drought in arid and semi-arid regions using PDSI and SDSM: a case study in Fars Province, Iran.JOURNAL OF ARID LAND,12(2),318-330.
MLA Dehghan, Sheida,et al."Prediction of meteorological drought in arid and semi-arid regions using PDSI and SDSM: a case study in Fars Province, Iran".JOURNAL OF ARID LAND 12.2(2020):318-330.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Dehghan, Sheida]'s Articles
[Salehnia, Nasrin]'s Articles
[Sayari, Nasrin]'s Articles
Baidu academic
Similar articles in Baidu academic
[Dehghan, Sheida]'s Articles
[Salehnia, Nasrin]'s Articles
[Sayari, Nasrin]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Dehghan, Sheida]'s Articles
[Salehnia, Nasrin]'s Articles
[Sayari, Nasrin]'s Articles
Terms of Use
No data!
Social Bookmark/Share

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.