AccScience Publishing / AJWEP / Volume 16 / Issue 3 / DOI: DOI 10.3233/AJW190038
RESEARCH ARTICLE

Efficiency of Modified Mixed Gamma Distribution in  Estimating Annual Maximum and Minimum Flows at  Moniya Gauging Station, Nigeria

Olusegun Sunday Ewemooje1* Temitayo Abayomi Ewemoje2
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1 Department of Statistics, Federal University of Technology, Akure, Nigeria
2 Agricultural and Environmental Engineering Department, University of Ibadan, Ibadan, Nigeria
AJWEP 2019, 16(3), 99–107; https://doi.org/DOI 10.3233/AJW190038
Submitted: 6 July 2017 | Revised: 17 October 2018 | Accepted: 17 October 2018 | Published: 19 July 2019
© 2019 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract

Reliable estimates of extreme flood flows are required for general flood risk management and planning.  To assess the risk and nature of flood discharge, modified mixed-gamma distribution was applied to different  plotting positions in taking care of shortfall in gamma distribution and how best it will estimate flood frequency  at Moniya Gauging Station along Ona River. Goodness of fit, minimum absolute difference (MAD) and root  mean square error (RMSE) between the observed and predicted flood flows were measured. Gamma distribution  matched with Weibull plotting position which gave the highest coefficient of determination (R2 ) of 0.9966; mixed  gamma with California gave 0.9947 while modified mixed gamma with Weibull gave 0.9964 respectively. The  MAD of 49.653, 3.123 and 20.922 at return periods of 50, 100, and 200-year obtained under the gamma when  matched with Weibull, California and Weibull plotting positions respectively. California gave minimal error with  the RMSE of 92.85 for gamma with some information lost, correcting for error incurred, Weibull gave minimal  errors of 159.20 and 93.91 for mixed gamma and modified mixed gamma distributions, respectively. Hence, we  conclude that modified mixed gamma distribution with Weibull plotting position is the most suitable for prediction  at the gauging station.

Keywords
Hydrologic modelling
modified mixed gamma
plotting position
statistical analysis
stream flow
Conflict of interest
The authors declare they have no competing interests.
References

Adegbola, A.A. and J.K. Jolayemi (2012). Historical rainfall-runoff modeling of river Ogunpa, Ibadan, Nigeria. Indian Journal of Science and Technology, 5(5), 2725-2728.


Brocca, L., Melone, F. and T. Moramarco (2011). Distributed rainfall-runoff modelling for flood frequency estimation and flood forecasting. Hydrological Processes, 25, 2801-2813. DOI: 10.1002/hyp.8042


Chin, D.A. (2006). Water Resources Engineering (2nd ed.). Pearson Prentice Hall, Upper Saddle River, New Jersey.


Ding, J., Wallner, M., Müller, H. and U. Haberlandt (2016). Estimation of instantaneous peak flows from maximum mean daily flows using the HBV hydrological model. Hydrological Processes, 30, 1431-1448. DOI: 10.1002/hyp.10725


Ehiorobo, J.O. and O.C. Izinyon (2013). Flood Frequency Analysis at Oshun River in Asejire Dam Site, Nigeria. Journal of Earth Science and Engineering, 3, 292-300.


Ewemoje, T.A. and O.S. Ewemooje (2011). Best distribution and plotting positions of daily maximum flood estimation at Ona River in Ogun-Oshun river basin, Nigeria. Agric. Eng. Int: CIGR Journal, 13(3), 1-11.


Ewemooje, O.S. (2014). Modelling Road Traffic Fatalities in Nigeria with Weibull Distribution. Advances in Agriculture, Sciences and Engineering Research, 4(4), 1595-1600.


Haan, C.T. (1994). Statistical Methods in Hydrology. Iowa State University Press. Ames.


Kedem, B., Chiu, L.S. and Z. Karni (1990). An analysis of the threshold method for measuring area-average rainfall. Journal of Applied Meteorology, 29, 3-20.


Maposa, D., Cochran, J.J. and M. Lesaoana (2014). Investigating the goodness-of-fit of ten candidate distributions and estimating high quantiles of extreme floods in the lower Limpopo River Basin, Mozambique. Journal of Statistics and Management Systems, 17(3), 265-283. DOI: 10.1080/09720510.2014.927602


Mudholkar, G.S., Srivastava, D.K. and M. Freimer (1995).The exponentiated Weibull family: A reanalysis of the bus-motor-failure data. Technometrics, 37(4), 436-445.


Ojha, G.S.P., Bernisson, R. and P. Bhunya (2008). Engineering Hydrology. Oxford University Press, New Delhi.


Oke, A.O., Sangodoyin, A.Y., Ogedengbe, K. and T. Omodele (2013). Mapping of River Water Quality using Inverse Weighted Interpolation in Ogun-Oshun River Basin, Nigeria. Landscape & Environment, 7(2), 48-62.


Piantadosi, J., Boland, J.W. and P.G. Howlett (2009). Simulation of rainfall totals on various time scales – Daily, Monthly and Yearly. Environmental Modeling and Assessment, 14(4), 431-438.


Rangeley, R., Thiam, B.M., Andersen, R.A. and C.A. Lyle (1994). International River Basin Organizations in Sub-Saharan Africa. World Bank Technical Paper Number 250, Africa Technical Department Series, The World Bank, Washington, D.C.


Rosenberg, K., Boland, J.W. and P.G. Howlett (2004). Simulation of monthly rainfall totals. ANZIAM Journal, 46(E), E85-E104.


Thom, H.C.S. (1968). Approximate Convolution of the Gamma and Mixed Gamma Distributions. Monthly Weather Review, 96(12), 883-886.


Topaloğlu, F. (2005). Regional Flood Frequency Analysis of the Basins of the East Mediterranean Region. Turkey Journal of Agric, 29, 287-295.


Wilson, E.M. (1990). Engineering Hydrology (4th ed.). Macmillan Press Ltd., London.


Yoo, C., Jung, K.-S. and T.-W. Kim (2005). Rainfall frequency analysis using a mixed Gamma distribution: Evaluation of the global warming effect on daily rainfall. Hydrological Processes, 19, 3851-3861. DOI: 10.1002/hyp.5985

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Asian Journal of Water, Environment and Pollution, Electronic ISSN: 1875-8568 Print ISSN: 0972-9860, Published by AccScience Publishing