Evaluation the Best Random Component in Modified Thomas-Fiering Model in Generating Rainfall Data for Akre station

Authors

DOI:

https://doi.org/10.25156/ptj.v9n2y2019.pp186-192

Keywords:

Thomas-Fiering, Rainfall, forecasting, Random component, Stochastic models

Abstract

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

Downloads

Download data is not yet available.

References

Barnes, J. W. 1994. Statistical Analysis for Engineer and Scientists. McGraw-Hill, Inc., USA.

Clark, R. T. 1984. Mathematical Models in Hydrology. FAO Consultant, Institute of Hydrology, Wallingford, UK.

Harms, A. A. and T. H. Campbell. 1967. An extension to the Thomas- Fiering model for the sequential generation of streamflow. Water Resour. Res. 3: 653-661.

Joshi, G. S. and K. Gupta. 2009. A simulation model for the operation of multipurpose multireservoir system for River Narmada. India. J. Hydro Environ. Res. 3: 96-108.

Kim, B. S., H. S. Kim and B. H. Seoh. 2004. Streamflow simulation and skewness preservation based on the bootstrapped stochastic models. Stoch. Environ. Res. Risk Asmt. 18(6): 386-400.

Kirby, W. 1972. Computer-oriented Wilson-Halfirty transform that preserves the first three moments are that lower bound of the Pearson Type 3 distribution. Water Resour. Res. 8(5): 1254- 1254.

Kurunç, A., K. Yurekli and O. Çevik. 2005. Performance of two stochastic approaches for forecasting water quality and stream flow data from Yesilirmak River. Turkey Environ. Mod. Softw. 20: 1195-1200.

McMahon, T. A. and A. J. Miller. 1971. Application of the Thomas- Fiering model to skewed hydrologic data. Water Resour. Res. 7:133e-134.

Payne, K., W. Human and D. Kern. 1969. Stream flow simulation. J. Hydrol. Dev. ASCE. 95: 1163-1179.

Srikanthan, R. 1978. Sequential generation of monthly stream flows. J. Hydrol. 38: 71-80.

Stedinger, J. R. and M. R. Taylor. 1982. Synthetic stream flow generation, 1. Model verification and validation. Water Resour. Res., 18(4): 909-918.

Thomas, H. A. and M. B. Fiering. 1962. Mathematical synthesis of stream flow sequences for the analysis of river basins by simulation. In: Design of Water Resources Systems. Harvard

University Press, Cambridge, Massachusetts. p459-493.

Wang, W. 2006. Stochasticity, Non Linearity and Forecasting of Stream Flow Processes, PhD Thesis. Technical University of Delft, Netherlands.

Wijayaratne, L. H. and P. C. Chan. 1987. Synthetic flow generation with stochastic models. In: Singh, V. P. editors. Flood Hydrology. Springer, Dordrecht. p175-185.

Yousif, A. A., F. K. Aswad and S. A. Ibrahim. 2016. Performance of ARIMA model and modified Thomas-Fiering model for predicting the monthly rainfall data for Tallafar station. J. Poly Tech. 6(1): 17

Volume 9 Number 2 (2019)

Downloads

Published

2019-12-10

How to Cite

Aswad, F. K., Yousif, A. A., & Ibrahim, S. A. (2019). Evaluation the Best Random Component in Modified Thomas-Fiering Model in Generating Rainfall Data for Akre station. Polytechnic Journal, 9(2), 186-192. https://doi.org/10.25156/ptj.v9n2y2019.pp186-192

Issue

Vol. 9 No. 2 (2019)

Section

Research Articles

License

Copyright (c) 2019 Fawaz Kh. Aswad, Ali A. Yousif, Sayran A. Ibrahim

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Authors who publish with this journal agree to the following terms:
1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License [CC BY-NC-ND 4.0] that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).