Evaluation of Statistical Methods for Estimating Missing Daily Streamflow Data

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YILMAZ M. U. , Önöz B.

TEKNIK DERGI, vol.30, no.6, pp.9597-9620, 2019 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 30 Issue: 6
  • Publication Date: 2019
  • Doi Number: 10.18400/tekderg.421091
  • Journal Name: TEKNIK DERGI
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.9597-9620
  • Istanbul Technical University Affiliated: Yes


In this study, it was aimed to investigate the applicability of various statistical estimation methods for the Porsuk River basin, which has sparse streamflow observations. Estimations were performed using regression analysis (REG), the single donor station based drainage area ratio (DAR), the multiple donor stations based drainage area ratio (MDAR), standardization with mean (SM), standardization with mean and standard deviation (SMS), inverse distance weighted (IDW) methods. Two separate studies were conducted for both partially missing data and completely missing data. In order to estimate streamflow statistics for use in SM and SMS methods, logarithmic regression equations were suggested. The promising results obtained from ensemble approaches will provide a significant hydrological contribution to streamflow estimations.