Evaluation the Best Random Component in Modified Thomas-Fiering Model in Generating Rainfall Data for Akre station
In this research, the effect of random component in the modified Thomas-Fiering model to generate daily rainfall data was studied, and Akre station considered a case study. A random component with special distributions: Normal random numbers, Wilson-Hilferty (W-H) transformation, truncated W-H, and...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Erbil Polytechnic University
2019-12-01
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| Series: | Polytechnic Journal |
| Subjects: | |
| Online Access: | https://polytechnic-journal.epu.edu.iq/home/vol9/iss2/30 |
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| Summary: | In this research, the effect of random component in the modified Thomas-Fiering model to generate
daily rainfall data was studied, and Akre station considered a case study. A random component
with special distributions: Normal random numbers, Wilson-Hilferty (W-H) transformation, truncated
W-H, and Kirby modification to W-H transformation were used. The model applied to the daily
rainfall data for Akre station for available years 2000–2006 and the model used to generate the
rainfall data for the years 2006 and 2007. The results showed that the correlation coefficients
between the observed and generated data were 0.82 for normal random numbers, 0.77 for W-H
transformation, 0.89 for truncated –W –H, and 0.87 for KM to W-H transformation. The tests
of Chi-square test, Kolmogorov–Smirnov test, root mean squared error (RMSE) test, and mean
absolute error (MAE) test were used to compare between observed and generated data. All the
results have passed the Chi-square test and Kolmogorov–Smirnov, where the calculated values
were less than the tabulated value at 5% significance. For the test RMSE and MAE, the truncated
W-H transform was the values of at least two. Therefore, W-H transform is the best for generating
the rainfall data at Akre station |
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| ISSN: | 2707-7799 |