Abstract
We present simulations of real flood and tsunami events using a hybrid OpenMP-MPI model on high-performance cluster systems. The two-dimensional shallow water equations were solved by means of the in-house code NUFSAW2D, using an edge-based cell-centred finite volume method with the central-upwind scheme for millions of unstructured cells, thus ensuring spatial accuracy, especially near buildings or hydraulic structures. Each node of a cluster system performed simulations using OpenMP and communicated with other nodes using MPI. We explain strategies on reordering the meshes to support contiguous memory access patterns and to minimise communication cost; to this end, a simple criterion was proposed to decide the strategy used. Despite employing static domain decompositions for such unstructured meshes, the computation loads were distributed dynamically based on the complexity level, to each core and node during runtime to ensure computational efficiency. Our model was tested by simulating two real-life cases: the 2011 flood event in Kulmbach (Germany) and the Japan 2011 tsunami recorded in Hilo Harbour, Hawaii (USA). The numerical results show that our model is robust and accurate when simulating such complex flood phenomena, while the hybrid parallelisation concept proposed proves to be quite efficient. We also provide an outlook for an advanced visualisation method employing the Sliding Window technique with an HDF5 data structure. With such a combination of high-performance computing and interactive visualisation, users have a comprehensive predictive tool to take immediate measures and to support decision makers in developing a well-integrated early warning system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Campolo M, Soldati A, Andreussi P (2003) Artificial neural network approach to flood forecasting in the River Arno. Hydrol Sci J 48(3):381–398. https://doi.org/10.1623/hysj.48.3.381.45286
Cheng C-T, Wang W-C, Xu D-M, Chau KW (2008) Optimizing hydropower reservoir operation using hybrid genetic algorithm and chaos. Water Resour Manage 22:895–909. https://doi.org/10.1007/s11269-007-9200-1
Ginting BM, Harlan D, Taufik A, Ginting H (2017) Optimization of reservoir operation using linear program, case study of Riam Jerawi Reservoir. Indonesia. Int J River Basin Manag 15(2):187–198. https://doi.org/10.1080/15715124.2017.1298604
Parkinson J, Mark O (2005) Urban stormwater management in developing countries, 2nd edn. IWA Publishing, London
Bhola PK, Leandro J, Disse M (2018) Framework for offline flood inundation forecasts for two-dimensional hydrodynamic models. Geosciences 8(9):1–19. https://doi.org/10.3390/geosciences8090346
Ginting BM, Mundani R-P (2018) Artificial viscosity technique: a Riemann-solver-free method for 2D urban flood modelling on complex topography. In: Gourbesville P, Cunge J, Caignaert G (eds) Advances in hydroinformatics. Springer water. Springer, Singapore, pp 51–74. https://doi.org/10.1007/978-981-10-7218-5_4
Ginting BM (2017) A two-dimensional artificial viscosity technique for modelling discontinuity in shallow water flows. Appl Math Model 45:653–683. https://doi.org/10.1016/j.apm.2017.01.013
Xilin X, Liang Q (2018) A new efficient implicit scheme for discretising the stiff friction terms in the shallow water equations. Adv Water Resour 117:87–97. https://doi.org/10.1016/j.advwatres.2018.05.004
Zhao J, Oezgen-Xian I, Liang D, Wang T, Hinkelmann R (2019) An improved multislope MUSCL scheme for solving shallow water equations on unstructured grids 77(2):576–596. https://doi.org/10.1016/j.camwa.2018.09.059
Hervouet JM (2000) A high-resolution 2-D dam-break model using parallelization. Hydrol Process 14(13):2211–2230. https://doi.org/10.1002/1099-1085(200009)14:13%3c2211:AID-HYP24%3e3.0.CO;2-8
Neal JC, Fewtrell TJ, Trigg M (2009) Parallelisation of storage cell flood models using OpenMP. Environ Model Softw 24(7):872–877. https://doi.org/10.1016/j.envsoft.2008.12.004
Sanders BF, Schubert JE, Detwiler RL (2010) Parbrezo: A parallel, unstructured grid, Godunov-type, shallow-water code for high-resolution flood inundation modeling at the regional scale. Adv Water Resour 33(12):1456–1467. https://doi.org/10.1016/j934.advwatres.2010.07.007
Tanaka S, Bunya S, Westerink JJ, Dawson C, Luettich RA Jr (2011) Scalability of an unstructured grid continuous Galerkin based hurricane storm surge model. J Sci Comput 46:329–358. https://doi.org/10.1007/s10915-010-9402-1
Arcos MEM, LeVeque RJ (2014) Validating velocities in the GeoClaw tsunami model using observations near Hawaii from the 2011 Tohoku tsunami. Pure Appl Geophys 17:849–867. https://doi.org/10.1007/s00024-014-0980-y
Meister O, Rahnema K, Bader M (2016) Parallel memory-efficient adaptive mesh refinement on structured triangular meshes with billions of grid cells. ACM T Math Softw 43(3):1–27. https://doi.org/10.1145/2947668
Wittmann R, Bungartz H-J, Neumann P (2017) High performance shallow water kernels for parallel overland flow simulations based on FullSWOF2D. Comput Math Appl 74(1):110–125. https://doi.org/10.1016/j.camwa.2017.01.005
Lai W, Khan AA (2017) A parallel two-dimensional discontinuous Galerkin method for shallow-water flows using high-resolution unstructured meshes. J Comput Civ Eng 31(3):1–10. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000647
Karypis G, Kumar V (1998) A fast and high quality multilevel scheme for partitioning irregular graphs. SIAM J Sci Comput 20(1):359–392. https://doi.org/10.1137/S1064827595287997
Ginting BM, Mundani R-P (2019) Parallel flood simulations for wet–dry problems using dynamic load balancing concept. J Comput Civ Eng 33(3):04019013. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000823
Ginting BM, Mundani R-P (2018) Rank E Parallel simulations of shallow water solvers for modelling overland flows. In: La Loggia G, Freni G, Puleo V, De Marchis M (eds) HIC 2018. EPiC series in engineering, vol 3, pp 788–799. https://doi.org/10.29007/wdn8
Ginting BM (2019) Central-upwind scheme for 2D turbulent shallow flows using high-resolution meshes with scalable wall functions. Comput Fluids 179:394–421. https://doi.org/10.1016/j.compfluid.2018.11.014
Ginting BM, Ginting H (2019) Hybrid artificial viscosity − central-upwind scheme for recirculating turbulent shallow water flows. J Hydraul Eng 145(12):04019041. https://doi.org/10.1061/(ASCE)HY.1943-7900.0001639
Ginting BM, Mundani R-P (2019) Comparison of shallow water solvers: Applications for dam-break and tsunami cases with reordering strategy for efficient vectorization on modern hardware. Water 11(4):639. https://doi.org/10.3390/w11040639
Mundani R-P, Frisch J, Varduhn V, Rank E (2015) A sliding window technique for interactive high-performance computing scenarios. Adv Eng Softw 84:21–30. https://doi.org/10.1016/j.advengsoft.2015.02.003
Ertl C, Frisch J, Mundani R-P (2017) Design and optimisation of an efficient HDF5 I/O Kernel for massive parallel fluid flow simulations. Concurrency Comput Pract Exp 29:1–12. https://doi.org/10.1002/cpe.4165
Kurganov A, Petrova G (2007) A second-order well-balanced positivity preserving central-upwind scheme for the Saint-Venant system. Commun Math Sci 5(1):133–160. https://doi.org/10.4310/CMS.2007.v5.n1.a6
https://xmswiki.com/wiki/SMS:2D_Mesh_Files_*.2dm. Accessed 15 Feb 2019
Nujić M (2014) Benutzerhandbuch, Hydro_AS-2D, 2D-Strömungsmodell für die wasserwirtschaftliche Praxis. HydrotecIngenieurgesell-schaft für Wasser und Umwelt mbH, Aachen (in German)
Disse M, Konnerth I, Bhola PK, Leandro J (2018) Unsicherheitsabschätzung für die Berechnung von Dynamischen Überschwemmungskarten – Fallstudie Kulmbach. In: Heimerl S (ed) Vorsorgender und nachsorgender Hochwasserschutz. Springer, Wiesbaden, pp 350–357. https://doi.org/10.1007/978-3-658-21839-3_50 (in German)
Bhola PK, Bhavna N, Leandro J, Rao SN, Disse M (2018) Flood inundation forecasts using validation data generated with the assistance of computer vision. J Hydroinform 21(2):240–256. https://doi.org/10.2166/hydro.2018.044
Bhola PK, Ginting BM, Leandro J, Broich K, Mundani RP, Disse M (2018) Model parameter uncertainty of a 2D hydrodynamic model for the assessment of disaster resilience, EnviroInfo, Garching, Munich, 5–7 September 2018
https://coastal.usc.edu/currents_workshop/index.html. Accessed 15 Feb 2019
https://lrz.de. Accessed 15 Feb 2019
Acknowledgements
Bobby Minola Ginting gratefully acknowledges the DAAD (German Academic Exchange Service), who supports his research in the scope of Research Grants—Doctoral Programmes in Germany 2015/16 (57129429). Punit Kumar Bhola and Markus Disse thank the Bavarian Water Authority and Bavarian Environment Agency in Hof for providing the data of Case 1—and gratefully acknowledge the German Federal Ministry of Education and Research for providing the funding in the scope of FloodEvac project (FKZ 13N13196). The compute and data resources provided by the Leibniz Supercomputing Centre are acknowledged. The contributions of Ugurcan Sari and Mengjie Zhao as the students in this work are highly appreciated.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Ginting, B.M., Bhola, P.K., Ertl, C., Mundani, RP., Disse, M., Rank, E. (2020). Hybrid-Parallel Simulations and Visualisations of Real Flood and Tsunami Events Using Unstructured Meshes on High-Performance Cluster Systems. In: Gourbesville, P., Caignaert, G. (eds) Advances in Hydroinformatics. Springer Water. Springer, Singapore. https://doi.org/10.1007/978-981-15-5436-0_67
Download citation
DOI: https://doi.org/10.1007/978-981-15-5436-0_67
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-5435-3
Online ISBN: 978-981-15-5436-0
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)