World Environmental and Water Resources Congress 2018
LP3 Flood Frequency Analysis Including Climate Change
Publication: World Environmental and Water Resources Congress 2018: Watershed Management, Irrigation and Drainage, and Water Resources Planning and Management
ABSTRACT
Hydrologists are concerned about possible climate change and trends in flood-flow frequency relationships. A proposal is to estimate the trends in the mean (sometimes also the variance) of floods over the period of record and employ the estimated trends to project the flood-risk distribution’s parameters into the future. How large do trends need to be for that to be attractive? This paper reports a Monte Carlo study based on the log-Pearson type 3 (LP3) distribution with estimated skewness coefficient, considering several variations of such a dynamic flood frequency analysis, and the estimation of parameters. With a sample size of 40 and small trends (within ±0.25% per year), the stationarity moment estimator is about the best among realistic moment methods across all cases considered regardless of the skewness coefficient; for larger trends one should incorporate the trend in the log-mean of the LP3 distribution; only for ±1% per year or more-extreme-trends in both the mean and variance was it advantageous to estimate the trends in both the log-mean and log-variance of the annual maximum series. The results show that the LP3 coefficient of skewness (which was assumed to be a constant and was estimated) has considerable effects on the efficiency of quantile and exceedance probability estimators in a dynamic world.
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REFERENCES
Bobée, B. (1975), The Log Pearson Type 3 Distribution and Its Application in Hydrology. Water Resources Research, 11(5), 681–689.
Bobée, B., and R. Robitaille (1977), The Use of the Pearson Type 3 and Log Pearson Type 3 Distributions Revisited. Water Resources Research, 13(2), 427–443.
Bobée, B., and Ashkar, F. (1991). The gamma family and derived distributions applied in hydrology. Water Resources Pubns. ISBN 0918334683.
Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer Series in Statistics. Springer-Verlag, London.
Chowdhury, J. U., and J. R. Stedinger (1991), Confidence Interval for Design Floods with Estimated Skew Coefficient, J. Hydraul. Eng., 117(7): 811–831
El Adlouni S.O., uarda, T.B.M.J., Zhang, X., Roy, R. et Bobée, B. (2007). Generalized maximum likelihood estimators for the nonstationary generalized extreme value model. Water Resour. Res.,43 (3): W03410.
England, J.F. Jr., Cohn, T.A., Faber, B.A., Stedinger, J.R., Thomas, W.O. Jr., Veilleux, A.G., Kiang, J.E., and Mason, R.R., 2017, Guidelines for Determining Flood Flow Frequency – Bulletin 17C: U.S. Geological Survey Techniques and Methodsbook 4, chap. B5, https://doi.org/10.3133/tm4-B5/
Griffis, V. W. (2003). Evaluation of log-Pearson type 3 flood frequency analysis methods addressing regional skew and low outliers. MS thesis, Cornell Univ., Ithaca, N.Y.
Griffis, V. W., J. R. Stedinger, and T. A. Cohn (2004), Log Pearson type 3 quantile estimators with regional skew information and low outlier adjustments. Water Resour. Res.,40, W07503.
Griffis, V. W., and J. R. Stedinger (2007a), The LP3 distribution and its application in flood frequency analysis, 1. Distribution Characteristics. J. Hydrol. Eng., 12(5), 482–491.
Griffis, V. W., and J. R. Stedinger (2007b), The LP3 distribution and its application in flood frequency analysis, 2. Parameter estimation methods, J. Hydrol. Eng.,12(5), 492–500.
Griffis, V. W., and J. R. Stedinger (2009), The log-Pearson type 3 distribution and its application in flood frequency analysis, 3. Sample skew and weighted skew estimators, J. Hydrol. Eng.,14(2), 209–212.
Gruber, A. M., and Stedinger, J. R. (2008). Models of LP3 regional skew, data selection, and Bayesian GLS regression. Proc., World Environmental & Water Resources Conf. 2008, R. Babcock and R. Walton, eds., ASCE, Reston, VA, Paper No. 596.
Hecht, S. Jory, and R. M. Vogel (2017), Updating design flood estimates using regression, Water Resources Research. Manuscript.
Hirsch, R. M. and Ryberg, K. R. (2012). Has the magnitude of floods across the USA changed with global CO2levels. Hydrological Sciences Journal, 57.1:1–9.
Hirsch, R. M. and S. A. Archfield (2016). Not higher but more often. Natural Climate Change,Vol 5, 198–199.
IPCC (2012). Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK, and New York NY, USA.
Jain, S. and Lall, U. (2001). Floods in a changing climate: does the past represent the future. Water Resources Research, 37.12:3193–3205.
Koutsoyiannis, D. and Montanari, A. (2007). Statistical analysis of hydroclimatic time series: Uncertainty and insights. Water Resour. Res., 43.5: W05429.
Lamontagne, J.R., J.R. Stedinger, Xin, Yu, C.A. Whealton, and Ziyao, Xu (2016). Robust Flood Frequency Analysis: Performance of EMA with Multiple Grubbs-Beck Outlier Tests. Water Resour. Res., 52(4), 3068–3084
Landwehr, J. M., and N. C. Matalas (1978), Some Comparisons of Flood Statistics in Real and Log Space. Water Resour. Res., 14.5:902–920.
Lins, H. F. and Slack, J. R. (1999). Streamflow trends in the United States. Geophysical Research Letters, 26.2:227–230.
Madsen, H., Lawrence, D., Lang, M., Martinkova, M., and Kjeldsen, T. (2013). A Review of Applied Methods in Europe for Flood-Frequency Analysis in a Changing Environment. FLOODFREQ COST Action ES0901. Center for Ecology & Hydrology.
Mentaschi, L. et al. (2016). The transformed-stationary approach: a generic and simplified methodology for non-stationary extreme value analysis. Hydrol. Earth Syst. Sci., 20, 3527–3547
Mîndrilă, D. (2010), Maximum Likelihood (ML) and Diagonally Weighted Least Squares (DWLS) Estimation Procedures: A Comparison of Estimation Bias with Ordinal and Multivariate Non-Normal Data, International Journal of Digital Society (IJDS), 1(1): 60–66
Parrett, C., Veilleux, A., Stedinger, J. R., Barth, N. A., Knifong, D. L., and Ferris, J. C. (2011), Regional skew for California, and flood frequency for selected sites in the Sacramento–San Joaquin River Basin, based on data through water year 2006,U.S. Geological Survey Scientific Investigations Report 2010–5260, 94 p.
Serago, M. Jake, and R. M. Vogle (2018), Parsimonious nonstationary flood frequency analysis, Advances in Water Resources, 112: pp. 1–16.
Stedinger, J. R. and Griffis, V. W. (2011). Getting from here to where? Flood frequency analysis and climate. JAWRA Journal of the American Water Resources Association, 47.3:506–513.
Tasker, G. D., and Stedinger, J. R. (1986). Estimating generalized skew with weighted least squares regression. J. Water Resour. Plann. Manage., 112(2): 225–237.
Veilleux, A. G., J. R. Stedinger, and J. R. Lamontagne (2011), Bayesian WLS/GLS Regression for Regional Skewness Analysis for Regions with Large Cross-Correlations among Flood Flows. World Environmental and Water Resources Congress: 3103–3112
Vogel, R. M., W. O. Thomas Jr., and T. A. McMahon (1993). Flood-flow frequency model selection in southwestern united states. Journal of Water Resources Planning and Management, 119(3), 353–366
Wasko, Conrad and Sharma, Ashish (2017), Global assessment of flood and storm extremes with increased temperatures, Scientific Report 7, Article number: 7045, Nature.
Weaver, J.C., Feaster, T.D., and Gotvald, A.J., (2009), Magnitude and frequency of rural floods in the Southeastern United States, through 2006—Volume 2, North Carolina: U.S. Geological Survey Scientific Investigations Report 2009–5158, 110 p.
White, H., and G. M. MacDonald (1980), Some Large-Sample Tests for Nonnormality in the Linear Regression Model. Journal of the American Statistical Associates, 75(369): 16–28.
Yu, Xin (2017), Flood Frequency Analysis in Context of Climate Change or with Mixed Populations, Ph.D. Dissertation, School of Civil and Environmental Engineering, Cornell University
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Published In
World Environmental and Water Resources Congress 2018: Watershed Management, Irrigation and Drainage, and Water Resources Planning and Management
Pages: 459 - 467
Editor: Sri Kamojjala, Las Vegas Valley Water District
ISBN (Online): 978-0-7844-8140-0
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© 2018 American Society of Civil Engineers.
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Published online: May 31, 2018
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