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Acceleration of flow modeling using a freeware 2D GPU-shallow water equations code

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Abstract

Excessive rainfall, storm surges and dam break are some of the serious Geohazards afflicting humankind. The non-structural technique to combat floods includes flood modeling which provides a complete flood history over an area of interest in the time domain. Over the past decades, a number of 1D and 2D hydraulic models have been developed to simulate floods; amongst these, the shallow water equations figure prominently as a potent model. However, these models suffer from a serious shortcoming, that is, of long run times, particularly for high resolution and large areas. A number of approaches and strategies have been proposed to remedy this issue, e.g. using models of reduced complexity, parallelization of algorithms and use of Graphical Processing Units (GPUs) to make the codes run faster. In this study, a freeware, 2D, GPU-enhanced code BASEMENT has been applied to three different test cases related to the laboratory and field. The results showed that, for lab-based cases, the GPU accelerated model was able to achieve a significant reduction in model execution time, attaining a Speedup ratio of 80, while for the field case the ratio was 8, which showed the potential of the GPU technology for flood inundation modeling. Further, the availability of a GPU-enhanced model in the public domain is very important to several scientific disciplines, e.g. Hydraulic Engineering, Flood Control and Management, Hazard Mitigation, etc.

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References

  • Alho P, Aaltonen J (2008) Comparing a 1D hydraulic model with a 2D hydraulic model for the simulation of extreme glacial outburst floods. Hydrol Processes: An Int J 22(10):1537–1547

    Article  Google Scholar 

  • Avesani D, Galletti A, Piccolroaz S, Bellin A, Majone BA (2021) A dual-layer MPI continuous large-scale hydrological model including Human Systems. Environ Model Softw 139:105003

    Article  Google Scholar 

  • Betsholtz A, Nordlöf B (2017) Potentials and limitations of 1D, 2D and coupled 1D-2D flood modelling in HEC-RAS. TVVR17/5003

  • Brodtkorb AR, Hagen TR, Sætra ML (2013) Graphics processing unit (GPU) programming strategies and trends in GPU computing. J Parallel Distribut Comput 73(1):4–13

    Article  Google Scholar 

  • Carlotto T, Chaffe PL, dos Santos CI, Lee S (2021) SW2D-GPU: a two-dimensional shallow water model accelerated by GPGPU. Environ Model Softw 145:105205

    Article  Google Scholar 

  • Chandran N, Gangodkar D, Mittal A (2018) A review on GPU programming strategies and recent trends in GPU computing. J Graphic Era Univ 6(2):207–223

    Google Scholar 

  • Chen AS, Evans B, Djordjević S, Savić DA (2012a) A coarse-grid approach to representing building blockage effects in 2D urban flood modelling. J Hydrol 426:1–16

    Google Scholar 

  • Chen AS, Evans B, Djordjević S, Savić DA (2012b) Multi-layered coarse grid modelling in 2D urban flood simulations. J Hydrol 470:1–11

    Google Scholar 

  • Dazzi S, Shustikova I, Domeneghetti A, Castellarin A, Vacondio R (2021) Comparison of two modelling strategies for 2D large-scale flood simulations. Environ Model Softw 146:105225

    Article  Google Scholar 

  • de la Asunción M, Mantas JM, Castro MJ (2010) Programming CUDA-based GPUs to simulate two-layer shallow water flows. Springer, European Conference on Parallel Processing

    Google Scholar 

  • De La Asunción M, Mantas JM, Castro MJ (2011) Simulation of one-layer shallow water systems on multicore and CUDA architectures. J Supercomput 58(2):206–214

    Article  Google Scholar 

  • Dullo TT, Kalyanapu AJ, Ghafoor SK, Marshall R, Tindall KJ, Anantharaj VG et al (2015) Computational Performance of an OpenMP-enabled, MPI-enabled and GPU-accelerated Two-dimensional Flood Model. In: AGU Fall Meeting Abstracts, Vol. 2015. pp NH51D-1930

  • Echeverribar I, Morales-Hernández M, Brufau P, García-Navarro P (2019) 2D numerical simulation of unsteady flows for large scale floods prediction in real time. Adv Water Resour 134:103444

    Article  Google Scholar 

  • Ekeu-wei IT, Blackburn GAJH (2018) Applications of open-access remotely sensed data for flood modelling and mapping in developing regions. Hydrology 5(3):39

    Article  Google Scholar 

  • Essaid M, Idoumghar L, Lepagnot J, Brévilliers M (2019) GPU parallelization strategies for metaheuristics: a survey. Int J Parallel Emerg Distrib Syst 34(5):497–522

    Article  Google Scholar 

  • Felder G, Zischg A, Weingartner RJJoh (2017) "The effect of coupling hydrologic and hydrodynamic models on probable maximum flood estimation. J Hydrol 550:157–165

    Article  Google Scholar 

  • Garland M, Le Grand S, Nickolls J, Anderson J, Hardwick J, Morton S, Phillips E, Zhang Y, Volkov V (2008) Parallel computing experiences with CUDA. IEEE Micro 28(4):13–27

    Article  Google Scholar 

  • Gharbi M, Soualmia A, Dartus D, Masbernat L (2016) Comparison of 1D and 2D hydraulic models for floods simulation on the Medjerda Riverin Tunisia. J Mater Environ Sci 7(8):3017–3026

    Google Scholar 

  • Ginting BM, Bhola PK, Ertl C, Mundani R-P, 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: Advances in Hydroinformatics. Springer, Singapore, pp 867–888

    Chapter  Google Scholar 

  • Goutiere L, Soares-Frazão S, Zech Y (2011) Dam-break flow on mobile bed in abruptly widening channel: experimental data. J Hydraul Res 49(3):367–371

    Article  Google Scholar 

  • Güneralp B, Güneralp İ, Liu Y (2015) Changing global patterns of urban exposure to flood and drought hazards. Glob Environ Chang 31:217–225

    Article  Google Scholar 

  • Haider S, Saeed U, Shahid M (2020) 2D numerical modeling of two dam-break flood model studies in an urban locality. Arab J Geosci 13(14):1–15

    Article  Google Scholar 

  • Han H, Hou J, Xu Z, Jing H, Gong J, Zuo D, Li B, Yang S, Kang Y, Wang R (2022) A GPU-accelerated hydrodynamic model for urban rainstorm inundation simulation: a case study in China. KSCE J Civ Eng 26(3):1494–1504

    Article  Google Scholar 

  • Hou J, Kang Y, Hu C, Tong Y, Pan B, Xia J (2020) A GPU-based numerical model coupling hydrodynamical and morphological processes. Int J Sediment Res 35(4):386–394

    Article  Google Scholar 

  • Hu X, Song L (2018) Hydrodynamic modeling of flash flood in mountain watersheds based on high-performance GPU computing. Nat Hazards 91(2):567–586

    Article  Google Scholar 

  • Huţanu E, Mihu-Pintilie A, Urzica A, Paveluc LE, Stoleriu CC, Grozavu A (2020) Using 1D HEC-RAS modeling and LiDAR data to improve flood hazard maps’ accuracy: a case study from Jijia floodplain (NE Romania). Water 12(6):1624

    Article  Google Scholar 

  • Kalyanapu AJ, Shankar S, Pardyjak ER, Judi DR, Burian SJ (2011) Assessment of GPU computational enhancement to a 2D flood model. Environ Model Softw 26(8):1009–1016

    Article  Google Scholar 

  • Kamal A (2004) Pakistan: Lai Nullah Basin Flood Problem Islamabad Rawalpindi Cities. World Meteorological Organization/Global Water Partnership. Associated Programme on Flood Management 1

  • Keckler SW, Dally WJ, Khailany B, Garland M, Glasco D (2011) GPUs and the future of parallel computing. IEEE Micro 31(5):7–17

    Article  Google Scholar 

  • Kim DE, Liong S-Y, Gourbesville P, Andres L, Liu JJW (2020) Simple-yet-effective SRTM DEM improvement scheme for dense urban cities using ANN and remote sensing data: application to flood modeling. Water 12(3):816

    Article  Google Scholar 

  • Ko CP, Chittem PK, Hsu CA, Alkhaleefah M, Huang MJ, Chang YL (2021) CUDA-enabled Programming for Accelerating Flood Simulation. In: 2021 the 5th International Conference on Graphics and Signal Processing, pp 72–75

  • Lacasta A, Morales-Hernández M, Murillo J, García-Navarro P (2015) GPU implementation of the 2D shallow water equations for the simulation of rainfall/runoff events. Environ Earth Sci 74(11):7295–7305

    Article  Google Scholar 

  • 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):04016073

    Article  Google Scholar 

  • Lea D, Yeonsu K, Hyunuk A (2019) Case study of HEC-RAS 1D–2D coupling simulation: 2002 Baeksan flood event in Korea. Water 11(10):2048

    Article  Google Scholar 

  • Liang Q, Smith LS (2015) A high-performance integrated hydrodynamic modelling system for urban flood simulations. J Hydroinf 17(4):518–533

    Article  Google Scholar 

  • Liang Q, Xia X, Hou JJPE (2016) Catchment-scale high-resolution flash flood simulation using the GPU-based technology. Proc Eng 154:975–981

    Article  Google Scholar 

  • Liu Q, Qin Y, Li G (2018) Fast simulation of large-scale floods based on GPU parallel computing. Water 10(5):589

    Article  Google Scholar 

  • Liu Z, Merwade V, Jafarzadegan K (2019) Investigating the role of model structure and surface roughness in generating flood inundation extents using one-and two-dimensional hydraulic models. J Flood Risk Manage 12(1):e12347

    Article  Google Scholar 

  • Marshall R, Ghafoor S, Rogers M, Kalyanapu A, Dullo TT (2018) Performance evaluation and enhancements of a flood simulator application for heterogeneous hpc environments. Int J Netw Comput 8(2):387–407

    Google Scholar 

  • Morales-Hernández M, Sharif MB, Kalyanapu A, Ghafoor SK, Dullo TT, Gangrade S, Kao S-C, Norman MR, Evans KJJEM (2021) TRITON: a multi-GPU open source 2D hydrodynamic flood model. Environ Model Softw 141:105034

    Article  Google Scholar 

  • Munoz DH, Constantinescu G (2018) A fully 3-D numerical model to predict flood wave propagation and assess efficiency of flood protection measures. Adv Water Resour 122:148–165

    Article  Google Scholar 

  • Neal J, Fewtrell T, Trigg M (2009) Parallelisation of storage cell flood models using OpenMP. Environ Model Softw 24(7):872–877

    Article  Google Scholar 

  • Neal JC, Fewtrell TJ, Bates PD, Wright NG (2010) A comparison of three parallelisation methods for 2D flood inundation models. Environ Model Softw 25(4):398–411

    Article  Google Scholar 

  • Neal J, Villanueva I, Wright N, Willis T, Fewtrell T, Bates P (2012) How much physical complexity is needed to model flood inundation? Hydrol Process 26(15):2264–2282

    Article  Google Scholar 

  • Neelima B, Raghavendra PS (2010) Recent trends in software and hardware for GPGPU computing: a comprehensive survey. In: 2010 5th International Conference on Industrial and Information Systems. IEEE, pp 319–324

  • Noh SJ, Lee J-H, Lee S, Kawaike K, Seo DJ (2018) Hyper-resolution 1D-2D urban flood modelling using LiDAR data and hybrid parallelization. Environ Model Softw 103:131–145

    Article  Google Scholar 

  • Patel RA, Zhang Y, Mak J, Davidson A, Owens JD (2012) Parallel lossless data compression on the GPU. IEEE, San Jose

    Book  Google Scholar 

  • Petaccia G, Leporati F, Torti E (2016) OpenMP and CUDA simulations of Sella Zerbino Dam break on unstructured grids. Comput Geosci 20(5):1123–1132

    Article  Google Scholar 

  • Rao P (2005) A parallel RMA2 model for simulating large-scale free surface flows. Environ Model Softw 20(1):47–53

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Sharif MB, Ghafoor SK, Hines TM, Morales-Hernändez M, Evans KJ, Kao SC et al (2020). Performance evaluation of a two-dimensional flood model on heterogeneous high-performance computing architectures. In: Proceedings of the Platform for Advanced Scientific Computing Conference, pp 1–9

  • Shustikova I, Domeneghetti A, Neal JC, Bates P, Castellarin A (2019) Comparing 2D capabilities of HEC-RAS and LISFLOOD-FP on complex topography. Hydrol Sci J 64(14):1769–1782

    Article  Google Scholar 

  • Soares-Frazão S, Zech Y (2007) Experimental study of dam-break flow against an isolated obstacle. J Hydraul Res 45(sup1):27–36

    Article  Google Scholar 

  • Vanzo D, Peter S, Vonwiller L, Buergler M, Weberndorfer M, Siviglia A, Conde D, Vetsch DF (2021) BASEMENT v3: a modular freeware for river process modelling over multiple computational backends. Environ Model Softw 143:105102

    Article  Google Scholar 

  • Vetsch D, Siviglia A, Ehrbar D, Facchini M, Gerber M, Kammerer S, Peter S, Vonwiler L, Volz C, Farshi D, Mueller R (2017) BASEMENT—basic simulation environment for computation of environmental flow and natural hazard simulation. Eidgenössische Technische Hochschule (ETH) Zurich, Zurich

    Google Scholar 

  • Vetsch DF, Vanzo D, Bürgler M, Bacigaluppi P, Conde D, Boes RM, Peter SJ, Vonwiller L, Siviglia A (2020) High performance computing in river modelling: a novel two-dimensional software for river hydro-and morphodynamic simulations. River Flow 2020, CRC Press:1401–1408

    Google Scholar 

  • Vu TT, Law AW, Nguyen TH, Chew AW (2019) Computational flood modeling with UPC architecture. J Comput Civ Eng 33(2):04019002

    Article  Google Scholar 

  • Wei N, Sun X, Bi X, Wang J-M, Li XJI, Chew AW (2019) The spatial characteristics of precipitation and water-logging disaster during rainy season for urban planning in Xi’an. J Comput Civ Eng 28(9):1263–1271

    Google Scholar 

  • Wong M, Parker G (2006) Reanalysis and correction of bed-load relation of Meyer-Peter and Müller using their own database. J Hydraul Eng 132(11):1159–1168

    Article  Google Scholar 

  • Wu Y, Tian L, Rubinato M, Gu S, Yu T, Xu Z, Cao P, Wang X, Zhao QJW (2020) A new parallel framework of SPH-SWE for dam break simulation based on OpenMP. Water 12(5):1395

    Article  Google Scholar 

  • Xia X, Liang Q, Ming X (2019) A full-scale fluvial flood modelling framework based on a high-performance integrated hydrodynamic modelling system (HiPIMS). Adv Water Resour 132:103392

    Article  Google Scholar 

  • Yang Z, Zhu Y, Pu Y (2008) Parallel image processing based on CUDA. In: 2008 International Conference on Computer Science and Software Engineering, vol. 3. IEEE,  pp 198-201

  • Zhang S, Xia Z, Yuan R, Jiang X (2014) Parallel computation of a dam-break flow model using OpenMP on a multi-core computer. J Hydrol 512:126–133

    Article  Google Scholar 

  • Zischg AP, Mosimann M, Bernet DB, Röthlisberger V (2018) Validation of 2D flood models with insurance claims. J Hydrol 557:350–361

    Article  Google Scholar 

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Acknowledgements

I would like to extend my wholehearted gratitude towards the faculty members Dr. Sajjad Haider, Dr. Hamza Farooq Gabriel and Dr. Muhammad Shahid of Department of Water Resources Engineering and Management, Nust Institute of Civil Engineering (NICE), National University of Sciences and Technology, Islamabad, Pakistan for all the times they supported me technically and morally. It was humble of them to spend their valuable time to teach and guide me throughout my research. The authors are also thankful for the very valuable comments which greatly improved the quality of the paper.

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Authors and Affiliations

  1. School of Civil & Environmental Engineering (SCEE), National University of Sciences and Technology, (NUST), Sector H-12, Islamabad, 44000, Pakistan

    Prince Mahmood, Sajjad Haider, Hamza Farooq Gabriel & Zain Syed

  2. Faculty of Civil Engineering, University of Engg. & Technology, 54890, Lahore, Pakistan

    Muhammad Shahid

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  1. Prince Mahmood
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  2. Sajjad Haider
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Mahmood, P., Haider, S., Gabriel, H.F. et al. Acceleration of flow modeling using a freeware 2D GPU-shallow water equations code. Arab J Geosci 15, 1584 (2022). https://doi.org/10.1007/s12517-022-10836-6

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