Comparison of Point Precipitation Frequency Analyses of Storm-Typed Maxima and Overall Maxima for a Region in Eastern Tennessee
Publication: Journal of Hydrologic Engineering
Volume 25, Issue 8
Abstract
In frequency analysis of point precipitation extremes, one approach that has been suggested is to segregate precipitation data by storm type. Thus, for short-duration (e.g., 2-h) extremes, only observations from convective storms would be considered in the analysis. The supposition informing this choice is that only convective events are capable of generating truly extreme 2-h precipitation depths. In this paper, annual maxima of 2-h point precipitation are evaluated for a region in eastern Tennessee using a storm-type database that identifies convective events. The use of storm typing contrasts with the standard procedure of using data from all storms to develop annual maxima series. This paper presents comparative frequency analyses of convective event and overall annual maxima series. For extremely low-probability events, predicted regional quantiles are slightly lower for convective event maxima than for annual maxima. However, differences between quantiles at individual sites vary widely. The convective event maxima series tend to have lower means, higher coefficients of variation, and slightly lower skewness (with great variability) than annual maxima series. Differences between extreme quantiles for convective event and annual maxima are correlated with differences in skewness. Overall, the differences between the regional results obtained from the convective event and annual maxima used in this study of 2-h precipitation are small, but differences at individual sites vary widely.
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Data Availability Statement
The DDST and the LH-moments routines used in the study were provided by third parties. Direct requests for these materials may be made to the providers indicated in the Acknowledgments.
The precipitation data and L-moments routines used in the study were obtained from the public domain and can be made available from the corresponding author by request. Several Fortran routines used in this study are proprietary and may only be provided with restrictions; interested parties should contact the corresponding author for further information.
Acknowledgments
The authors wish to acknowledge the Tennessee Valley Authority for courteously making the DDST available through M. G. Schaefer, and Q. T. Wang for generously sharing the Fortran routines for implementing the LH-moments approach.
Disclaimer
This work of authorship and those incorporated herein were prepared by Consolidated Nuclear Security, LLC (CNS) as accounts of work sponsored by an agency of the United States Government under Contract DE-NA0001942. Accordingly, the US Government retains a paid-up, nonexclusive, irrevocable, worldwide license to publish or reproduce this work for US Government purposes only. Neither the United States Government nor any agency thereof, nor CNS, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility to any non-governmental recipient hereof for the accuracy, completeness, use made, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency or contractor thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency or contractor (other than the authors) thereof.
References
ARR (Australian Rainfall and Runoff). 2016. “Australian rainfall and runoff: A guide to flood estimation.” Accessed April 14, 2019. http://arr.ga.gov.au/arr-guideline.
Deka, S., M. Borah, and S. C. Kakaty. 2011. “Statistical analysis of annual maximum rainfall in north-east India: An application of LH-moments.” Theor. Appl. Climatol. 104 (1–2): 111–122. https://doi.org/10.1007/s00704-010-0330-7.
DOE (US Department of Energy). 2017. Natural phenomena hazards analysis and design criteria for DOE facilities. DOE-STD-1020-2016. Washington, DC: DOE.
Garavaglia, F., J. Gailhard, E. Paquet, M. Lang, R. Garcon, and P. Berndardara. 2010. “Introducing a rainfall compound distribution model based on weather patterns sub-sampling.” Hydrol. Earth Syst. Sci. 14 (6): 951–964. https://doi.org/10.5194/hess-14-951-2010.
Hirschboeck, K. K. 2003. “Respecting the drainage divide: A perspective on hydroclimatological change and scale.” Univ. Counc. Water Resour. (126): 48–53.
Hosking, J. R. M. 2005. “Version 3.04 of the L-moments code. A collection of 56 Fortran-77 routines for statistical analysis using L-moments, and some auxiliary routines used by the L-moment routines.”. Yorktown Heights, NY: T.J. Watson Research Center, IBM Research Division.
Hosking, J. R. M., and J. R. Wallis. 2005. Regional frequency analysis: An approach based on L-moments, 224. New York: Cambridge University Press.
Institute of Hydrology. 1999. Flood estimation handbook. Wallingford, UK: UK Centre for Ecology and Hydrology.
Kunkel, K. E., D. R. Easterling, D. A. Kristovich, B. Gleason, L. Stoecker, and R. Smith. 2012. “Meteorological causes of the secular variations in observed extreme precipitation events for the conterminous United States.” J. Hydrometeorol. 13 (3): 1131–1141. https://doi.org/10.1175/JHM-D-11-0108.1.
Lawrimore, J. 2017. Algorithm theoretical basis document, hourly precipitation data (HPD) automated system, version 1 beta release HPD-auto/ATBD, version 1.0.0 / February 1, 2017. Silver Spring, MD: National Oceanic and Atmospheric Administration.
MetStat, Inc. 2018. Trinity River hydrologic hazards project task 2—Storm typing for the trinity River Basin. Washington, DC: USACE.
NOAA and NCDC (National Oceanic and Atmospheric Administration and National Climatic Data Center). 2003. Data documentation for data set 3240 (DSI-3240), hourly precipitation data. Asheville, NC: NOAA.
NOAA (National Oceanic and Atmospheric Administration). 2006. “Precipitation-frequency atlas of the United States.” In NOAA Atlas 14, Volume 2, version 3.0, Ohio River valley and surrounding states, edited by G. M. Bonnin, D. Martin, B. Lin, T. Parzybok, M. Yekta, and D. Riley. Silver Spring, MD: NOAA National Weather Service.
NOAA (National Oceanic and Atmospheric Administration). 2013. “Precipitation-frequency atlas of the United States, Southeastern States.” In NOAA Atlas 14 Volume 9 Version 2.0, edited by S. Perica, D. Martin, S. Pavlovic, I. Roy, M. St. Laurent, C. Trypaluk, D. Unruh, M. Yekta, and G. Bonnin. Silver Spring, MD: NOAA National Weather Service.
Papalexiou, S. M., and D. Koutsoyiannis. 2013. “Battle of extreme value distributions: A global survey on extreme daily rainfall.” Water Resour. Res. 49 (1): 187–201. https://doi.org/10.1029/2012WR012557.
Schaefer, M., B. Barker, S. Carney, W. Gibson, D. Martin, T. Parzybok, and G. Taylor. 2015. “Regional precipitation-frequency analyses for mid-latitude cyclones, mesoscale storms with embedded convection, local storms and tropical storm remnant storm types in the Tennessee Valley watershed.” Accessed February 3, 2015. http://www.mgsengr.com/damsafetyfiles/TVA_Point%20Precipitation-Frequency_2015-03-02_Release.pdf.
Serinaldi, F., and C. G. Kilsby. 2014. “Rainfall extremes: Toward reconciliation after the battle of distributions.” Water Resour. Res. 50 (1): 336–352. https://doi.org/10.1002/2013WR014211.
Stedinger, J. 2017. “Flood frequency analysis.” In Handbook of applied hydrology, edited by V. P. Singh, 2nd ed. New York: McGraw-Hill.
USBR (US Bureau of Reclamation). 2004. Hydrologic hazard curve estimating procedures. Denver: Dam Safety Research Program.
Wang, Q. J. 1997. “LH moments for statistical analysis of extreme events.” Water Resour. Res. 33 (12): 2841–2848. https://doi.org/10.1029/97WR02134.
Zucchini, W., and P. T. Adamson. 1989. “Bootstrap confidence intervals for design storms from exceedance series.” Hydrol. Sci. J. 34 (1): 41–48. https://doi.org/10.1080/02626668909491307.
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©2020 American Society of Civil Engineers.
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Received: Jul 7, 2019
Accepted: Feb 10, 2020
Published online: Jun 12, 2020
Published in print: Aug 1, 2020
Discussion open until: Nov 12, 2020
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