Iguniwari Thomas Ekeu-Wei^1,2*, George Alan Blackburn¹, Jason Giovannettone³

Show more
¹ Lancaster Environmental Centre, Lancaster University, Lancaster, UK.
² Kawari Technical Services Nigeria Limited, Yenagoa, Nigeria.
³ Dewberry, 8401 Arlington Blvd., Fairfax, Virginia, USA.
Show less

Abstract: Extreme flood events are becoming more frequent and intense in recent times, owing to climate change and other anthropogenic factors. Nigeria, the case-study for this research experiences recurrent flooding, with the most disastrous being the 2012 flood event that resulted in unprecedented damage to infrastructure, displacement of people, socio-economic disruption, and loss of lives. To mitigate and minimize the impact of such floods now and in the future, effective planning is required, underpinned by analytics based on reliable data and information. Such data are seldom available in many developing regions, owing to financial, technical, and organizational drawbacks that result in short-length and inadequate historical data that are prone to uncertainties if directly applied for flood frequency estimation. This study applies regional Flood Frequency Analysis (FFA) to curtail deficiencies in historical data, by agglomerating data from various sites with similar hydro-geomorphological characteristics and is governed by a similar probability distribution, differing only by an “index-flood”; as well as accounting for climate variability effect. Data from 17 gauging stations within the Ogun-Osun River Basin in Western Nigeria were analysed, resulting in the delineation of 3 sub-regions, of which 2 were homogeneous and 1 heterogeneous. The Generalized Logistic distribution was fitted to the annual maximum flood series for the 2 homogeneous regions to estimate flood magnitudes and the probability of occurrence while accounting for climate variability. The influence of climate variability on flood estimates in the region was linked to the Madden-Julian Oscillation (MJO) climate indices and resulted in increased flood magnitude for regional and direct flood frequency estimates varying from 0% - 35% and demonstrate that multi-decadal changes in atmospheric conditions influence both small and large floods. The results reveal the value of considering climate variability for flood frequency analysis, especially when non-stationarity is established by homogeneity analysis.

Keywords: Climate Variability, Regional Flood Frequency, Climate-Indices, L-Moment, Madden-Julian Oscillation (MJO), Generalised Logistic (GLO), Climate-Indices

Cite this paper: Ekeu-Wei, I. , Blackburn, G. and Giovannettone, J. (2020) Accounting for the Effects of Climate Variability in Regional Flood Frequency Estimates in Western Nigeria. Journal of Water Resource and Protection, 12, 690-713. doi: 10.4236/jwarp.2020.128042.

References

[1]   Tehrany, M.S., Pradhan, B. and Jebur, M.N. (2014) Flood Susceptibility Mapping Using a Novel Ensemble Weights-of-Evidence and Support Vector Machine Models in GIS. Journal of Hydrology, 512, 332-343.
https://doi.org/10.1016/j.jhydrol.2014.03.008

[2]   The Federal Government of Nigeria (2013) Post-Disaster Needs Assessment 2012 Floods.
https://www.gfdrr.org/sites/gfdrr/files/NIGERIA_PDNA_PRINT_05_29_2013_WEB.pdf

[3]   Agada, S. and Nirupama, N. (2015) A Serious Flooding Event in Nigeria in 2012 with Specific Focus on Benue State: A Brief Review. Natural Hazards, 77, 1405-1414.
https://doi.org/10.1007/s11069-015-1639-4

[4]   Hosking, J.R.M. and Wallis, J.R. (1997) Regional Frequency Analysis: An Approach Based on L-Moments. Cambridge University Press, Cambridge, New York.
https://doi.org/10.1017/CBO9780511529443

[5]   Kjeldsen, T.R., Smithers, J.C. and Schulze, R.E. (2002) Regional Flood Frequency Analysis in the KwaZulu-Natal Province, South Africa, Using the Index-Flood Method. Journal of Hydrology, 255, 194-211.
https://doi.org/10.1016/S0022-1694(01)00520-0

[6]   Mishra, B., Takara, K., Yamashiki, Y. and Tachikawa, Y. (2009) Hydrologic Simulation-Aided Regional Flood Frequency Analysis of Nepalese River Basins. Journal of Flood Risk Management, 2, 243-253.
https://doi.org/10.1111/j.1753-318X.2009.01041.x

[7]   Ampadu, B., Chappell, N.A. and Kasei, R.A. (2013) Rainfall-River Flow Modelling Approaches: Making a Choice of Data-Based Mechanistic Modelling Approach for Data Limited Catchments: A Review. Canadian Journal of Pure and Applied Sciences, 7, 2571-2580.

[8]   Olayinka, D.N., Nwilo, P.C. and Emmanuel, A. (2013) From Catchment to Reach: Predictive Modelling of Floods in Nigeria.

[9]   Dano Umar, L., et al. (2011) Geographic Information System and Remote Sensing Applications in Flood Hazards Management: A Review. Research Journal of Applied Sciences, Engineering and Technology, 3, 933-947.

[10]   Reed, D. (1999) Procedures for Flood Frequency Estimation, Volume 3: Statistical Procedures for Flood Frequency Estimation. Institute of Hydrology, Parker.

[11]   Hrachowitz, M., et al. (2013) A Decade of Predictions in Ungauged Basins (PUB)—A Review. Hydrological Sciences Journal, 58, 1198-1255.
https://doi.org/10.1080/02626667.2013.803183

[12]   Wagener, T. (2007) Can We Model the Hydrological Impacts of Environmental Change? Hydrological Processes, 21, 3233-3236.
https://doi.org/10.1002/hyp.6873

[13]   Smith, A., Sampson, C. and Bates, P. (2015) Regional Flood Frequency Analysis at the Global Scale. Water Resources Research, 51, 539-553.
https://doi.org/10.1002/2014WR015814

[14]   Owe, M. and Neale, C. (2007) Remote Sensing for Environmental Monitoring and Change Detection (No. 316). International Assn of Hydrological Sciences.

[15]   Kunkel, K. (2003) North American Trends in Extreme Precipitation. Natural Hazards, 29, 291-305.
https://doi.org/10.1023/A:1023694115864

[16]   Pettitt, A. (1979) A Non-Parametric Approach to the Change-Point Problem. Applied Statistics, 28, 126-135.
https://doi.org/10.2307/2346729

[17]   Kendall, M. and Stuart, A. (1969) The Advanced Theory of Statistics (Volume 1). Griffin, London.

[18]   O’Brien, N.L. and Burn, D.H. (2014) A Nonstationary Index-Flood Technique for Estimating Extreme Quantiles for Annual Maximum Streamflow. Journal of Hydrology, 519, 2040-2048.
https://doi.org/10.1016/j.jhydrol.2014.09.041

[19]   Hounkpè, J., Diekkrüger, B., Badou, D.F. and Afouda, A.A. (2015) Non-Stationary Flood Frequency Analysis in the Ouémé River Basin, Benin Republic. Hydrology, 2, 210-229.
https://doi.org/10.3390/hydrology2040210

[20]   Li, J. and Tan, S. (2015) Nonstationary Flood Frequency Analysis for Annual Flood Peak Series, Adopting Climate Indices and Check Dam Index as Covariates. Water Resources Management, 29, 5533-5550.
https://doi.org/10.1007/s11269-015-1133-5

[21]   Adeaga, O., Oyebande, L. and Depraetere, C. (2006) Surface Runoff Simulation for Part of Yewa Basin. In: Predictions in Ungauged Basins: Promise and Progress, No. 303, IAHS Publ., Wallingford, 382.

[22]   Adeleke, O.O., Makinde, V., Eruola, A.O., Dada, O.F., Ojo, A.O. and Aluko, T.J. (2015) Estimation of Groundwater Recharges Using Empirical Formulae in Odeda Local Government Area, Ogun State, Nigeria. Challenges, 6, 271-281.
https://doi.org/10.3390/challe6020271

[23]   Komolafe, A.A., et al. (2015) A Review of Flood Risk Analysis in Nigeria. American Journal of Environmental Sciences, 11, 157-166.
https://doi.org/10.3844/ajessp.2015.157.166

[24]   Mouhamed, L., Traore, S.B., Alhassane, A. and Sarr, B. (2013) Evolution of Some Observed Climate Extremes in the West African Sahel. Weather and Climate Extremes, 1, 19-25.
https://doi.org/10.1016/j.wace.2013.07.005

[25]   New, M., et al. (2006) Evidence of Trends in Daily Climate Extremes over Southern and West Africa. Journal of Geophysical Research: Atmospheres, 111, D14102.
https://doi.org/10.1029/2005JD006289

[26]   Diatta, S. and Fink, A.H. (2014) Statistical Relationship between Remote Climate Indices and West African Monsoon Variability. International Journal of Climatology, 34, 3348-3367.
https://doi.org/10.1002/joc.3912

[27]   Salau, O.R., Fasuba, A., Aduloju, K.A., Adesakin, G.E. and Fatigun, A.T. (2016) Effects of Changes in ENSO on Seasonal Mean Temperature and Rainfall in Nigeria. Climate, 4, 5.
https://doi.org/10.3390/cli4010005

[28]   Olukanni, D. and Alatise, M. (2008) Rainfall-Runoff Relationships and Flow Forecasting, Ogun River Nigeria. Journal of Environmental Hydrology, 16, 1-12.

[29]   Ewemoje, T.A. and Ewemooje, O. (2011) Best Distribution and Plotting Positions of Daily Maximum Flood Estimation at Ona River in Ogun-Oshun River Basin, Nigeria. Agricultural Engineering International: CIGR Journal, 13, 1-10.

[30]   Rohatgi, A. (2017) Web Plot Digitizer.
https://automeris.io/WebPlotDigitizer

[31]   Farr, T.G., et al. (2007) The Shuttle Radar Topography Mission. Reviews of Geophysics, 45, RG2004.
https://doi.org/10.1029/2005RG000183

[32]   GCOS-AOPC/PPOC. Download Climate Time Series.
http://www.esrl.noaa.gov/psd/gcos_wgsp/Timeseries

[33]   Ekeu-wei, I.T., Blackburn, G.A. and Pedruco, P. (2018) Infilling Missing Data in Hydrology: Solutions Using Satellite Radar Altimetry and Multiple Imputation for Data-Sparse Regions. Water, 10, 1483.
https://doi.org/10.3390/w10101483

[34]   Mann, H.B. (1945) Nonparametric Tests against Trend. Econometrica: Journal of the Econometric Society, 13, 245-259.
https://doi.org/10.2307/1907187

[35]   Yue, S. and Wang, C. (2002) The Influence of Serial Correlation on the Mann– Whitney Test for Detecting a Shift in Median. Advances in Water Resources, 25, 325-333.
https://doi.org/10.1016/S0309-1708(01)00049-5

[36]   Stedinger, J.R. (1983) Estimating a Regional Flood Frequency Distribution. Water Resources Research, 19, 503-510.
https://doi.org/10.1029/WR019i002p00503

[37]   Pedruco, P., Nielsen, C., Kuczera, G. and Rahman, A. (2014) Combining Regional Flood Frequency Estimates with an at Site Flood Frequency Analysis Using a Bayesian Framework: Practical Considerations. In: Hydrology and Water Resources Symposium, ACT: Engineers Australia, Barton, 766-773.

[38]   Grubbs, F.E. and Beck, G. (1972) Extension of Sample Sizes and Percentage Points for Significance Tests of Outlying Observations. Technometrics, 14, 847-854.
https://doi.org/10.1080/00401706.1972.10488981

[39]   Kwon, H.H., Brown, C. and Lall, U. (2008) Climate Informed Flood Frequency Analysis and Prediction in Montana Using Hierarchical Bayesian Modeling. Geophysical Research Letters, 35, L05404.
https://doi.org/10.1029/2007GL032220

[40]   Gutiérrez, F. and Dracup, J.A. (2001) An Analysis of the Feasibility of Long-Range Streamflow Forecasting for Colombia Using El Ni?o-Southern Oscillation Indicators. Journal of Hydrology, 246, 181-196.
https://doi.org/10.1016/S0022-1694(01)00373-0

[41]   Sayers, P., et al. (2015) Strategic Flood Management: Ten “Golden Rules” to Guide a Sound Approach. International Journal of River Basin Management, 13, 137-151.
https://doi.org/10.1080/15715124.2014.902378

[42]   Machado, M.J., Botero, B.A., López, J., Francés, F., Díez-Herrero, A. and Benito, G. (2015) Flood Frequency Analysis of Historical Flood Data under Stationary and Non-Stationary Modelling. Hydrology and Earth System Sciences Discussions, 12, 525-568.
https://doi.org/10.5194/hessd-12-525-2015

[43]   Giovannettone, J.P. (2015) Correlating MJO Activity with Argentina Rainfall and Atlantic Hurricanes Using ICI-RAFT. Journal of Hydrologic Engineering, 22, E5015004.

[44]   Giovannettone, J. and Wright, M. (2011) The ICI-WARM Non-Proprietary Regional Frequency Analysis Tool Using the Method of L-Moments. AGU Fall Meeting, Vol. 1, 1016.

[45]   Dalrymple, T. (1960) Flood-Frequency Analyses, Manual of Hydrology: Part 3. USGPO.

[46]   Padi, P.T., Baldassarre, G.D. and Castellarin, A. (2011) Floodplain Management in Africa: Large Scale Analysis of Flood Data. Physics and Chemistry of the Earth, 36, 292-298.
https://doi.org/10.1016/j.pce.2011.02.002

[47]   Izinyon, O. and Ajumka, H. (2013) Regional Flood Frequency Analysis of Catchments in Upper Benue River Basin Using Index Flood Procedure. Nigerian Journal of Technology, 32, 159-169.

[48]   Stedinger, J.R. and Griffis, V.W. (2008) Flood Frequency Analysis in the United States: Time to Update. Journal of Hydrologic Engineering, 13, 199-204.
https://doi.org/10.1061/(ASCE)1084-0699(2008)13:4(199)

[49]   Izinyon, O. and Ehiorobo, J. (2014) L-Moments Approach for Flood Frequency Analysis of River Okhuwan in Benin-Owena River Basin in Nigeria. Nigerian Journal of Technology, 33, 10-18.
https://doi.org/10.4314/njt.v33i1.2

[50]   Komi, K., Amisigo, B.A., Diekkrüger, B. and Hountondji, F.C. (2016) Regional Flood Frequency Analysis in the Volta River Basin, West Africa. Hydrology, 3, 5.
https://doi.org/10.3390/hydrology3010005

[51]   Adeaga, O. (2006) Multi-Decadal Variability of Rainfall and Water Resources in Nigeria. In: Climate Variability and Change—Hydrological Impacts, IAHS Publication No. 308, Wallingford, 294.

[52]   Oyegoke, S. and Oyebande, L. (2008) A New Technique for Analysis of Extreme Rainfall for Nigeria. Environmental Research Journal, 2, 7-14.

[53]   Federal Ministry of Environment (2005) Technical Guidelines on Soil Erosion, Flood and Coastal Zone Management.

[54]   Peel, M., Wang, Q.J., Vogel, R. and McMahon, T. (2001) The Utility of L-Moment Ratio Diagrams for Selecting a Regional Probability Distribution. Hydrological Sciences Journal, 46, 147-155.
https://doi.org/10.1080/02626660109492806

[55]   Hailegeorgis, T.T. and Alfredsen, K. (2017) Regional Flood Frequency Analysis and Prediction in Ungauged Basins Including Estimation of Major Uncertainties for Mid-Norway. Journal of Hydrology: Regional Studies, 9, 104-126.
https://doi.org/10.1016/j.ejrh.2016.11.004

[56]   Leclerc, M. and Ouarda, T.B.M.J. (2007) Non-Stationary Regional Flood Frequency Analysis at Ungauged Sites. Journal of Hydrology, 343, 254-265.
https://doi.org/10.1016/j.jhydrol.2007.06.021

[57]   Hall, J., et al. (2014) Understanding Flood Regime Changes in Europe: A State-of-the-Art Assessment. Hydrology and Earth System Sciences, 18, 2735-2772.
https://doi.org/10.5194/hess-18-2735-2014

[58]   Madden, R.A. and Julian, P.R. (1971) Detection of a 40-50 Day Oscillation in the Zonal Wind in the Tropical Pacific. Journal of the Atmospheric Sciences, 28, 702-708.
https://doi.org/10.1175/1520-0469(1971)028<0702:DOADOI>2.0.CO;2

[59]   Mohino, E., Janicot, S., Douville, H. and Li, L. (2012) Impact of the Indian Part of the Summer MJO on West Africa Using Nudged Climate Simulations. Climate Dynamics, 38, 2319-2334.
https://doi.org/10.1007/s00382-011-1206-y

[60]   Lavender, S.L. and Matthews, A.J. (2009) Response of the West African Monsoon to the Madden-Julian Oscillation. Journal of Climate, 22, 4097-4116.
https://doi.org/10.1175/2009JCLI2773.1

[61]   ACMAD (2012) Flood Report over West Africa—September 2012. African Centre of Meteorological Applications for Development (ACMAD).
http://reliefweb.int/sites/reliefweb.int/files/resources/FloodreportoverWestAfrica.pdf

[62]   Arnold, N., Branson, M., Kuang, Z., Randall, D. and Tziperman, E. (2015) MJO Intensification with Warming in the Superparameterized CESM. Journal of Climate, 28, 2706-2724.
https://doi.org/10.1175/JCLI-D-14-00494.1

[63]   Caballero, R. and Huber, M. (2010) Spontaneous Transition to Superrotation in Warm Climates Simulated by CAM3. Geophysical Research Letters, 37, L11701.
https://doi.org/10.1029/2010GL043468

[64]   Sheng, H., et al. (2020) Frequency and Magnitude Variability of Yalu River Flooding: Numerical Analyses for the Last 1000 Years. Hydrology and Earth System Sciences.
https://doi.org/10.5194/hess-2019-582

[65]   López, J. and Francés, F. (2013) Non-Stationary Flood Frequency Analysis in Continental Spanish Rivers, Using Climate and Reservoir Indices as External Covariates. Hydrology and Earth System Sciences, 17, 3189-3203.
https://doi.org/10.5194/hess-17-3189-2013

[66]   Serinaldi, F., Kilsby, C.G. and Lombardo, F. (2018) Untenable Nonstationarity: An Assessment of the Fitness for Purpose of Trend Tests in Hydrology. Advances in Water Resources, 111, 132-155.
https://doi.org/10.1016/j.advwatres.2017.10.015