Technical Papers
Aug 19, 2022

Urban Design Storm Hyetograph Analysis Based on a New Method Considering Spatiotemporal Variations

Publication: Journal of Hydrologic Engineering
Volume 27, Issue 11

Abstract

Design storms guarantee uniformity regarding quality and operation standards of engineering projects and have been employed widely in urban drainage system design. Commonly used urban design storms, such as the Chicago (K-C) storm and Pilgrim and Cordery (P-C) storm, are calculated using prescribed or historical hyetographs. A prescribed hyetograph is unsuitable for a particular urban region in most cases, and a historical hyetograph takes no account of the spatiotemporal variations between the rainfall pattern at the rain station and that within the calculated region. Additionally, neither method can make adaptive adjustments for climate change. To obtain a more practical design storm with consideration of spatiotemporal variations and climatic changes, this study introduced proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) to urban design storm study. To demonstrate the feasibility and advantages of the proposed methodology, four cities (London, New York, Sydney, Wuhan) in different continents with different climatic characteristics were selected as case studies. The principal results are as follows. (1) Breaking the assumption of a uniform precipitation distribution, the proposed DMD-POD method is effective in capturing design storms under current climatic conditions and is sufficiently flexible to adapt to climate change. (2) The low-order representation of the rainfall field indicates substantial change in the storm patterns in urban areas. The peak discharge in New York and Wuhan is almost 10% higher than before urbanization, while that in Sydney and London is more than 10% lower on average. The peak time is largely unchanged in New York and Sydney, while it is 4 and 5 h later in London and Wuhan, respectively. (3) Compared with the K-C storm and P-C storm, the flood peak of POD storm increases and appears slightly earlier. The flood peak time in Wuhan simulated with the POD storm is 1 h (2 h) earlier than that simulated with the K-C storm (P-C storm). The peak flow obtained by the POD storm is 9.55% (25.05%) greater than that obtained by the K-C storm (P-C storm), which means that the POD design storm demands a higher level of safety for an engineering project under the same return period.

Get full access to this article

View all available purchase options and get full access to this article.

Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

This research is supposed by the National Natural Science Foundation of China (No. 41890823) and the National Key Research and Development Program of China (No. 2019YFC0408901). We express our gratitude to the reviewers and editors for their comments on the manuscript. We thank James Buxton, MSc, from Edanz (www.liwenbianji.cn/), for editing the English text of a draft of this manuscript.

References

Alam, M. S., and A. Elshorbagy. 2015. “Quantification of the climate change-induced variations in intensity–duration–frequency curves in the Canadian prairies.” J. Hydrol. 527 (Aug): 990–1005. https://doi.org/10.1016/j.jhydrol.2015.05.059.
Arnell, V., P. Harremoës, M. Jensen, N. B. Johansen, and J. Niemczynowicz. 1984. “Review of rainfall data application for design and analysis.” J. Water Sci. Technol. 16 (8–9): 1–45. https://doi.org/10.2166/wst.1984.0176.
Aubry, N. 1991. “On the hidden beauty of the proper orthogonal decomposition.” Theor. Comput. Fluid Dyn. 2 (5): 339–352. https://doi.org/10.1007/BF00271473.
Brunton, B. W., L. A. Johnson, J. G. Ojemann, and J. N. Kutz. 2016. “Extracting spatial-temporal coherent patterns in large-scale neural recordings using dynamic mode decomposition.” J. Neurosci. Methods 258 (Jan): 1–15. https://doi.org/10.1016/j.jneumeth.2015.10.010.
Cen, G., S. Jin, and R. Fan. 1998. “Research on rainfall pattern of urban design storm.” Adv. Water Sci. 9 (1): 42–47.
Cheveigné, A. D., and J. Z. Simon. 2007. “Denoising based on time-shift PCA.” J. Neurosci. Methods 165 (2): 297–305. https://doi.org/10.1016/j.jneumeth.2007.06.003.
Dey, P., and P. P. Mujumdar. 2019. “On the uniformity of rainfall distribution over India.” J. Hydrol. 578 (Nov): 124017. https://doi.org/10.1016/j.jhydrol.2019.124017.
Eckart, C., and G. Young. 1936. “The approximation of one matrix by another of lower rank.” Psychometrika 1 (3): 211–218. https://doi.org/10.1007/BF02288367.
Erichson, N. B., and C. Donovan. 2016. “Randomized low-rank dynamic mode decomposition for motion detection.” Comput. Vision Image Understanding 146 (May): 40–50. https://doi.org/10.1016/j.cviu.2016.02.005.
Everson, R. M., L. Sirovich, M. Winter, and T. J. Barben. 1970. “Eigenfunction analysis of turbulent mixing phenomena.” AIAA J. 30 (7): 329–339. https://doi.org/10.1007/3-540-54899-8_55.
Ghimire, G. R., N. Jadidoleslam, R. Goska, and W. F. Krajewski. 2021. “Insights into storm direction effect on flood response.” J. Hydrol. 600 (1): 126683. https://doi.org/10.1016/j.jhydrol.2021.126683.
Gong, Y., X. Liang, X. Li, J. Li, and R. Song. 2016. “Influence of rainfall characteristics on total suspended solids in urban runoff: A case study in Beijing, China.” Water 8 (7): 278. https://doi.org/10.3390/w8070278.
Greenbaum, A. 1997. “Iterative methods for solving linear systems || 2. Some iteration methods.” Soc. Ind. Appl. Math. XIII 2 (1): 123–181.
Han, S., and B. Feeny. 2003. “Application of proper orthogonal decomposition to structural vibration analysis.” Mech. Syst. Sig. Process. 17 (5): 989–1001. https://doi.org/10.1006/mssp.2002.1570.
Hershfield, D. M. 1961. “Estimating the probable maximum precipitation.” Am. Soc. Civ. Eng. 87 (5): 99–106.
Higham, J. E., et al. 2017. “Using modal decompositions to explain the sudden expansion of the mixing layer in the wake of a groyne in a shallow flow.” Adv. Water Resour. 107 (Sep): 451–459. https://doi.org/10.1016/j.advwatres.2017.05.010.
Higham, J. E., W. Brevis, and C. J. Keylock. 2018. “Implications of the selection of a particular modal decomposition technique for the analysis of shallow flows.” J. Hydraul. Res. 56 (6): 796–805. https://doi.org/10.1080/00221686.2017.1419990.
Huff, F. A. 1968. “Spatial distribution of heavy storm rainfalls in Illinois.” Water Resour. Res. 4 (1): 47–54. https://doi.org/10.1029/WR004i001p00047.
Jovanovic, M. R., P. J. Schmid, and J. W. Nichols. 2014. “Sparsity-promoting dynamic mode decomposition.” Phys. Fluids 26 (2): 561–571.
Karhunen, K. 1946. “Zur spektral theorie stochasticher prozesse.” Ann. Academiae Sci. Fennicae 34: 1–7.
Kiefer, C. J., and H. H. Chu. 1957. “Synthetic storm pattern for drainage design.” J. Hydraulics Div. 83 (4): 1–25. https://doi.org/10.1061/JYCEAJ.0000104.
Kutz, N. J., S. L. Brunton, B. W. Brunton, and J. L. Proctor. 2016. Dynamic mode decomposition: Data-driven modeling of complex systems. Philadelphia: Society for Industrial and Applied Mathematics.
Lima, C. H., H. H. Kwon, and J. Y. Kim. 2016. “A Bayesian beta distribution model for estimating rainfall IDF curves in a changing climate.” J. Hydrol. 540 (Sep): 744–756. https://doi.org/10.1016/j.jhydrol.2016.06.062.
Lin, G. F., and B. C. Jhong. 2015. “A real-time forecasting model for the spatial distribution of typhoon rainfall.” J. Hydrol. 521 (Feb): 302–313. https://doi.org/10.1016/j.jhydrol.2014.12.009.
Liu, M., L. Tan, and S. Cao. 2020. “Method of dynamic mode decomposition and reconstruction with application to a three-stage multiphase pump.” Energy. 208 (Oct): 118343. https://doi.org/10.1016/j.energy.2020.118343.
Loève, M. 1963. Probability theory. 3rd ed. New York: D. Van Nostrand Company.
Lu, H., and D. M. Tartakovsky. 2019. “Lagrangian dynamic mode decomposition for construction of reduced-order models of advection-dominated phenomena.” J. Comput. Phys. 15 (Apr): 109229. https://doi.org/10.1016/j.jcp.2020.109229.
Mann, J., and J. N. Kutz. 2015. “Dynamic mode decomposition for financial trading strategies.” Quant. Finance 16 (11): 1643–1655. https://doi.org/10.1080/14697688.2016.1170194.
Marsalek, J., and W. E. Watt. 1984. “Design storms for urban drainage design.” Can. J. Civ. Eng. 11 (3): 574–584. https://doi.org/10.1139/l84-075.
Meric, G., C. Lentz, W. Smeltz, and I. Meric. 2012. “International evidence on market linkages after the 2008 stock market crash.” Int. J. Bus. Finance Res. 6 (4): 45–57.
Palynchuk, B. A., and Y. Guo. 2011. “A probabilistic description of rain storms incorporating peak intensities.” J. Hydrol. 409 (1–2): 71–80. https://doi.org/10.1016/j.jhydrol.2011.07.040.
Pan, C., X. Wang, L. Liu, H. Huang, and D. Wang. 2017. “Improvement to the Huff curve for design storms and urban flooding simulations in Guangzhou, China.” Water 9 (6): 411. https://doi.org/10.3390/w9060411.
Pilgrim, D. H., and I. Cordery. 1975. “Rainfall temporal patterns for design floods.” J. Hydraulics Div. 101 (1): 81–95. https://doi.org/10.1061/JYCEAJ.0004197.
Rempala, G. A. 2012. “Inference for discretely observed stochastic kinetic networks with applications to epidemic modeling.” Biostatistics 13 (1): 153–165. https://doi.org/10.1093/biostatistics/kxr019.
Rowley, C. W., T. Colonius, and R. M. Murray. 2004. “Model reduction for compressible flows using POD and Galerkin projection.” Phys. D 189 (1–2): 115–129. https://doi.org/10.1016/j.physd.2003.03.001.
Rui, X., C. Jiang, and Q. Chen. 2015. “Hydrological problems for engineering of drainage and water log prevention in urban areas.” Adv. Sci. Technol. Water Resour. 35 (1): 42–48.
Rulli, F., S. Fontanesi, A. D’Adamo, and F. Berni. 2019. “A critical review of flow field analysis methods involving proper orthogonal decomposition and quadruple proper orthogonal decomposition for internal combustion engines.” Int. J. Engine Res. 22 (1): 222–242. https://doi.org/10.1177/1468087419836178.
Schmid, P. J. 2011. “Application of the dynamic mode decomposition to experimental data.” Exp. Fluids 50 (4): 1123–1130. https://doi.org/10.1007/s00348-010-0911-3.
Schmid, P. J., and J. Sesterhenn. 2010. “Dynamic mode decomposition of numerical and experimental data.” J. Fluid Mech. 656 (10): 5–28. https://doi.org/10.1017/S0022112010001217.
Sirovich, L. 1987. “Turbulence and the dynamics of coherent structures, part III: Dynamics and scaling, quarterly of applied mathematics.” Q. Appl. Math. 45 (3): 583–590. https://doi.org/10.1090/qam/910464.
Varraso, R., J. Garcia-Aymerich, F. Monier, N. L. Moual, J. D. Batlle, G. Miranda, C. Pison, I. Romieu, F. Kauffmann, and J. Maccario. 2012. “Assessment of dietary patterns in nutritional epidemiology: Principal component analysis compared with confirmatory factor analysis.” Am. J. Clin. Nutr. 96 (5): 1079–1092. https://doi.org/10.3945/ajcn.112.038109.
Wahidi, R., S. M. Olcmen, and J. P. Hubner. 2018. “Different approaches to applying POD analysis to 3D3C data in a large measurement volume.” Fluid Mech. Res. 45 (3): 187–201. https://doi.org/10.1615/InterJFluidMechRes.2018020625.
Wang, A., N. Qu, Y. Chen, L. Qi, and S. Gu. 2018. “A 60-minute design rainstorm for the urban area of Yangpu district, Shanghai, China.” Water 10 (3): 312. https://doi.org/10.3390/w10030312.
Wang, J. 1987. “Study of design storms in China.” J. Hydrol. 96 (1–4): 279–291. https://doi.org/10.1016/0022-1694(87)90159-4.
Watt, W. E., K. Chow, W. D. Hogg, and K. W. Lathem. 2011. “A 1-h urban design storm for Canada.” Can. J. Civ. Eng. 13 (3): 293–300. https://doi.org/10.1139/l86-041.
Xia, J., K. M. O’Connor, R. K. Kachroo, and G. C. Liang. 1997. “A non-linear perturbation model considering catchment wetness and its application in river flow forecasting.” J. Hydrol. 200 (1–4): 164–178. https://doi.org/10.1016/S0022-1694(97)00013-9.
Xia, J., G. Wang, G. Tan, Y. E. Aizhong, and G. H. Huang. 2005. “Development of distributed time-variant gain model for nonlinear hydrological systems.” Sci. China 48 (6): 713–723.
Yen, B. C., and V. T. Chow. 1980. “Design hyetographs for small drainage structures.” J. Hydraulics Div. 106 (6): 1055–1076. https://doi.org/10.1061/JYCEAJ.0005442.

Information & Authors

Information

Published In

Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 27Issue 11November 2022

History

Received: Apr 16, 2021
Accepted: May 25, 2022
Published online: Aug 19, 2022
Published in print: Nov 1, 2022
Discussion open until: Jan 19, 2023

Permissions

Request permissions for this article.

Authors

Affiliations

Ph.D. Candidate, State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan Univ., Wuhan 430072, China; Hubei Key Lab of Water System Science for Sponge City Construction, Wuhan 430072, China. Email: [email protected]
Xiang Zhang [email protected]
Professor, State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan Univ., Wuhan 430072, China; Hubei Key Lab of Water System Science for Sponge City Construction, Wuhan 430072, China (corresponding author). Email: [email protected]
Feng Xiong, Ph.D. [email protected]
Bureau of Hydrology, Changjiang Water Resources Commission, Wuhan 430010, China. Email: [email protected]
Xincheng Wang [email protected]
Ph.D. Candidate, State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan Univ., Wuhan 430072, China. Email: [email protected]
Ph.D. Candidate, State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan Univ., Wuhan 430072, China; Hubei Key Lab of Water System Science for Sponge City Construction, Wuhan 430072, China. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share