Estimation of Intensity-Duration-Frequency (IDF) Curves from Large Scale Atmospheric Dataset by Statistical Downscaling

Alramlawi K., FISTIKOĞLU O.

TEKNIK DERGI, cilt.33, sa.1, ss.11591-11616, 2022 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 33 Sayı: 1
  • Basım Tarihi: 2022
  • Doi Numarası: 10.18400/tekderg.874035
  • Dergi Adı: TEKNIK DERGI
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.11591-11616
  • Anahtar Kelimeler: Statistical downscaling, bias correction, quantile mapping, rainfall disaggregation, IDF curve, CLIMATE-CHANGE, ERA-INTERIM, REANALYSIS DATA, DAILY PRECIPITATION, BIAS CORRECTION, LOCAL CLIMATE, RIVER-BASIN, NCEP-NCAR, MODEL, RAINFALL
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

The study proposes a new approach that combined statistical downscaling, bias correction, and disaggregation of rainfall techniques to derive the IDF curve from large scale atmospheric reanalysis data. The applied methodology details the NCEP/NCAR reanalysis dataset being downscaled by an ANN-based approach to estimate the daily rainfall of Izmir. The annual maximum rainfall series of the study area were sampled from the daily downscaled rainfall series. The sampled daily maximum rainfalls were then bias-corrected by the quantile mapping method and disaggregated into the annual maximum standard duration rainfall heights regarding the rainfalls' scale-invariant properties. Finally, the IDF curves of the study area were determined by using the disaggregated rainfall heights. The results confirmed that the IDF curves dependent on short-duration extreme rainfall heights could be reasonably estimated from the large-scale atmospheric variables using the statistical downscaling approach.