In this study, it was aimed to investigate applicability of various statistical estimation methods for Porsuk River basin, which has sparse streamflow observations. Estimations were performed using regression, single and multiple donor stations based drainage area ratio, standardization with mean (SM), standardization with mean and standard deviation (SMS), inverse distance weighted methods. Two seperate 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.
In this study, it was aimed to investigate applicability of various statistical estimation methods for Porsuk River basin, which has sparse streamflow observations. Estimations were performed using regression, single and multiple donor stations based drainage area ratio, standardization with mean (SM), standardization with mean and standard deviation (SMS), inverse distance weighted methods. Two seperate 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.
Primary Language | English |
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Subjects | Civil Engineering |
Journal Section | Articles |
Authors | |
Publication Date | November 1, 2019 |
Submission Date | May 4, 2018 |
Published in Issue | Year 2019 Volume: 30 Issue: 6 |