PROBABILISTIC REGIONAL METEOROLOGICAL DROUGHT ANALYSIS WITH STANDARDIZED PRECIPITATION INDEX AND NORMAL PRECIPITATION INDEX METHODS IN GEOGRAPHIC INFORMATION SYSTEMS ENVIRONMENT: A CASE STUDY IN SEYHAN BASIN

Creative Commons License

Keskiner A. D., ÇETİN M., Simsek M., Akin S., Cetiner I.

FRESENIUS ENVIRONMENTAL BULLETIN, cilt.28, sa.7, ss.5675-5688, 2019 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 28 Sayı: 7
  • Basım Tarihi: 2019
  • Dergi Adı: FRESENIUS ENVIRONMENTAL BULLETIN
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED)
  • Sayfa Sayıları: ss.5675-5688
  • Çukurova Üniversitesi Adresli: Evet

Özet

Drought indices are useful tools to characterize and monitor drought conditions in a region. Primary objectives of this research were to: 1) develop regional meteorological drought maps of Sand 10-year return periods by using drought indices of Standardized Precipitation Index (SPI) and Percent of Normal Index (PNI), 2) investigate changes in drought classes by the methods used. Long-term (1950-2006) annual and monthly precipitation series of 63 meteorological stations located in the Seyhan River basin of Turkey were utilized in the study. Because the SPI method does not allow missing data in precipitation series, data were completed by regression analysis through utilizing nearby station's data. Frequency analysis was performed on SPI series of monthly data calculated for 12-month time-scale and annual total precipitation series. The most suitable probability distribution models for the series were determined by Kolmogorov-Smirnov goodness-of-fit test at 5% significance level. SPI of 5- and 10-year recurrence intervals and yearly precipitation amounts with 2-, 5- and 10 year return periods for each station were determined from probability distribution models. PNI of 5- and 10-year return periods were calculated, too. Maps of SPI and PNI values with return period of 5- and 10-year were generated by using Ordinary Co-kriging interpolation technique. Drought classes of SPI with a given return period did not generally match up with PNI drought classes. Drought with return period of 10-year or over would be evaluated as potentially risky in Seyhan Basin. Droughts by SPI were less influenced from mean precipitation fluctuations compared to PNI.

ABSTRACT
Dought indices are useful tools to characterize and monitor drought conditions in a region. Primary objectives of this research were to 1) develop regional meteorological drought maps of 5- and 10-year return periods by using drought indices of Standardized Precipitation Index (SPI) and Per- cent of Normal Index (PNI), 2) investigate changes in drought classes by the methods used. Long-term (1950-2006) annual and monthly precipitation se- ries of  63 meteorological stations located in the Seyhan River basin of
Turkey were utilized in the study. Because the SPI method does not allow missing data in precipitation series, data were com- pleted by regression analysis through utilizing nearby station's data. Frequency analysis was per- formed on SPI series of monthly data calculated for 12-month time-scale and annual total precipitation series. The most suitable probability distribution models for the series were determined by Kolmogo- rov-Smirnov goodness-of-fit test at 5% significance level. SPI of 5- and 10-year recurrence intervals and yearly precipitation amounts with 2-, 5- and 10- year return periods for each station were deter- mined from probability distribution models. PNI of 5- and 10-year return periods were calculated, too. Maps of SPI and PNI values with return period of 5- and 10-year were generated by using Ordinary Co-kriging interpolation technique. Drought classes of SPI with a given return period did not generally match up with PNI drought classes. Drought with return period of 10-year or over would be evaluated as
potentially risky in Seyhan Basin. Droughts by SPI were less influenced from mean precipitation fluctuations compared to PNI.
KEYWORDS: Seyhan Basin, SPI, PNI, Recurrence Interval, Drought