Review of the algebraic linear methods and parallel implementation in numerical simulation of groundwater flow

CHENG Tang-pei; LIU Xing-wei; SHAO Jing-Li; CUI Ya-li

Volume 4 Issue 1

Mar. 2016

Turn off MathJax

Article Contents

Article Navigation > Journal of Groundwater Science and Engineering > 2016 > 4(1): 12-17

CHENG Tang-pei, LIU Xing-wei, SHAO Jing-Li, et al. 2016: Review of the algebraic linear methods and parallel implementation in numerical simulation of groundwater flow. Journal of Groundwater Science and Engineering, 4(1): 12-17.

Citation:

CHENG Tang-pei, LIU Xing-wei, SHAO Jing-Li, et al. 2016: Review of the algebraic linear methods and parallel implementation in numerical simulation of groundwater flow. Journal of Groundwater Science and Engineering, 4(1): 12-17.

Citation:

PDF( 116 KB)

Review of the algebraic linear methods and parallel implementation in numerical simulation of groundwater flow

1Institute of Applied Physics and Computational Mathematics, Beijing 100088, China.2CAEP Software Center for High Performance Numerical Simulation, Beijing 100088, China.3School of Water Resources and Environmental Science, China University of Geosciences (Beijing), Beijing 100083, China.

Publish Date: 2016-03-28

Abstract

Abstract

The desire to increase spatial and temporal resolution in modeling groundwater system has led to the requirement for intensive computational ability and large memory space. In the course of satisfying such requirement, parallel computing has played a core role over the past several decades. This paper reviews the parallel algebraic linear solution methods and the parallel implementation technologies for groundwater simulation. This work is carried out to provide guidance to enable modelers of groundwater systems to make sensible choices when developing solution methods based upon the current state of knowledge in parallel computing.
- Groundwater flow simulation,
- Parallel algebraic algorithms,
- Krylov subspace methods,
- Preconditioning,
- GPU computing,
- Parallel computing framework

FullText(HTML)

References(16)

References

DONG Yan-hui, LI Guo-ming. 2009. A parallel PCG solver for MODFLOW. Groundwater. 47(6): 845-850.

Miller C T, Dawson C N, et al. 2013. Numerical simulation of water resources problems: Models, methods, and trends. Advances in Water Resources, (51): 405-437.

JI X H, CHENG T P, et al. 2012. CUDA-based solver for large-scale groundwater flow simulation. Engineering with Computers, 28(1): 13-19.

ZHANG K N, WU Y S, Bodvarsson G S. 2003. Parallel computing simulation of fluid flow in the unsaturated zone of Yucca Mountain, Nevada. Journal of Contaminant Hydrology, 62-63(2): 381-399.

TANG G P, D'Azevedo E F, et al. 2010. Application of a hybrid MPI/OpenMP approach for parallel groundwater model calibration using multi-core computers. Com?puters & Geosciences, 36(11): 1451- 1460.

Harbaugh A W. 2005. MODFLOW-2005, the US geological survey modular groundwater model: The groundwater flow process. Reston, VA, USA: US Department of the Interior, US Geological Survey.

Knoll D A, Keyes D E. 2004. Jacobian-free Newton-Krylov methods: A survey of approaches and applications. Journal of Computational Physics. 193(2): 357-397.

Saad Y. 2003. Iterative methods for sparse linear systems. Philadelphia: Society for Industrial and Applied Mathematics.

Hwang H T, Park Y J, et al. 2014. A parallel computational framework to solve flow and transport in integrated surface-subsurface hydrologic systems. Environmental Model?ling & Software, 61: 39-58.

Hughes J D, White J T. 2013. Use of general purpose graphics processing units with MODFLOW. Groundwater, 51(6): 833-846.

Nakajima K. 2011. Parallel multigrid solvers using openmp/mpi hybrid programming models on multi-core/multi-socket clusters. In: High Performance Computing for Computational Science-Vecpar 2010. Berlin: Springer.

Le P V V, Kumar P, et al. 2015. GPU-based high-performance computing for integrated surface-sub-surface flow modeling. Environ?mental Modelling & Software, 73: 1-13.

Hammond G E, Lichtner P C, Mills R T. 2014. Evaluating the performance of parallel subsurface simulators: An illustrative example with PFLOTRAN. Water Resources Research, 50(1): 208-228.

CHENG Tang-pei, SHAO Jing-li, et al. 2014b. Parallel simulation of groundwater flow in the North China Plain. Journal of Earth Science, 25(6): 1059-1066.

Dongarra J J, Foster I, et al. 2003. Sourcebook of parallel computing. San Francisco: Morgan Kaufmann Publishers.

CHENG Tang-pei, MO Ze-yao, SHAO Jing-li. 2014a. Accelerating groundwater flow simulation in MODFLOW using JASMIN- Based parallel computing. Groundwater, 52(2): 194-205.

Relative Articles

[1]	Adla Andalu, M Gopal Naik, Sandeep Budde, 2026: AI and ML in groundwater exploration and water resources management: Concepts, methods, applications, and future directions, Journal of Groundwater Science and Engineering, 14, 100-122. doi: 10.26599/JGSE.2026.9280059
[2]	Mobin Eftekhari, Abbas Khashei-Siuki, 2025: Evaluating machine learning methods for predicting groundwater fluctuations using GRACE satellite in arid and semi-arid regions, Journal of Groundwater Science and Engineering, 13, 5-21. doi: 10.26599/JGSE.2025.9280035
[3]	Jwan Sabah Mustafa, Dana Khider Mawlood, 2024: Developing three-dimensional groundwater flow modeling for the Erbil Basin using Groundwater Modeling System (GMS), Journal of Groundwater Science and Engineering, 12, 178-189. doi: 10.26599/JGSE.2024.9280014
[4]	Liu Yang, Yan-pei Cheng, Xue-ru Wen, Jun Liu, 2024: Development, hotspots and trend directions of groundwater numerical simulation: A bibliometric and visualization analysis, Journal of Groundwater Science and Engineering, 12, 411-427. doi: 10.26599/JGSE.2024.9280031
[5]	Jun Zhang, Rong-zhe Hou, Kun Yu, Jia-qiu Dong, Li-he Yin, 2024: Impact of water table on hierarchically nested groundwater flow system, Journal of Groundwater Science and Engineering, 12, 119-131. doi: 10.26599/JGSE.2024.9280010
[6]	Qing-shan Li, Xiao-bing Kang, Mo Xu, Bang-yan Mao, 2023: Effects of coal mining and tunnel excavation on groundwater flow system in karst areas by modeling: A case study in Zhongliang Mountain, Chongqing, Southwest China, Journal of Groundwater Science and Engineering, 11, 391-407. doi: 10.26599/JGSE.2023.9280031
[7]	Yi-hang Gao, Jun-hui Shen, Lin Chen, Xiao Li, Shuang Jin, Zhen Ma, Qing-hua Meng, 2023: Influence of underground space development mode on the groundwater flow field in Xiong’an new area, Journal of Groundwater Science and Engineering, 11, 68-80. doi: 10.26599/JGSE.2023.9280007
[8]	Temesgen Mekuriaw Manderso, Yitbarek Andualem Mekonnen, Tadege Aragaw Worku, 2023: Application of GIS based analytical hierarchy process and multicriteria decision analysis methods to identify groundwater potential zones in Jedeb Watershed, Ethiopia, Journal of Groundwater Science and Engineering, 11, 221-236. doi: 10.26599/JGSE.2023.9280019
[9]	Feng-dan Yu, Gang Qiao, Kai Wang, Xu Zhang, 2023: Investigation of groundwater characteristics and its influence on Landslides in Heifangtai Plateau using comprehensive geophysical methods, Journal of Groundwater Science and Engineering, 11, 171-182. doi: 10.26599/JGSE.2023.9280015
[10]	Chun-chao ZHANG, Xin-wei HOU, Xiang-quan LI, Zhen-xing WANG, Chun-lei GUI, Xue-feng ZUO, Jian-fei MA, Ming GAO, 2020: Numerical simulation and environmental impact prediction of karst groundwater in Sangu Spring Basin, China, Journal of Groundwater Science and Engineering, 8, 210-222. doi: 10.19637/j.cnki.2305-7068.2020.03.002
[11]	ZHU Heng-hua, JIA Chao, XU Yu-liang, YU Ze-min, YU Wei-jiang, 2018: Study on numerical simulation of organic pollutant transport in groundwater northwest of Laixi, Journal of Groundwater Science and Engineering, 6, 293-305. doi: 10.19637/j.cnki.2305-7068.2018.04.005
[12]	GUO Chun-yan, CUI Ya-li, LIU Wen-na, CUI Xiang-xiang, FEI Yu-hong, 2018: Research on numerical simulation of the groundwater funnels restoration in Shijiazhuang, Journal of Groundwater Science and Engineering, 6, 126-135. doi: 10.19637/j.cnki.2305-7068.2018.02.006
[13]	LI Lu-lu, SU Chen, HAO Qi-chen, SHAO Jing-li, 2018: Numerical simulation of response of groundwater flow system in inland basin to density changes, Journal of Groundwater Science and Engineering, 6, 7-17. doi: 10.19637/j.cnki.2305-7068.2018.01.002
[14]	TONG Shao-qing, DONG Yan-hui, ZHANG Qian, SONG Fan, 2017: Visualizing complex pore structure and fluid flow in porous media using 3D printing technology and LBM simulation, Journal of Groundwater Science and Engineering, 5, 254-265.
[15]	MA Luan, WANG Guang-cai, SHI Zhe-ming, GUO Yu-ying, XU Qing-yu, HUANG Xu-juan, 2016: Simulation of groundwater level recovery in abandoned mines, Fengfeng coalfield, China, Journal of Groundwater Science and Engineering, 4, 344-353.
[16]	WEI Jia-hua, CHU Hai-bo, WANG Rong, JIANG Yuan, 2015: Numerical simulation of karst groundwater system for discharge prediction and protection design of spring in Fangshan District, Beijing, Journal of Groundwater Science and Engineering, 3, 316-330.
[17]	, 2014: The Experimental Investigations on Motion Features of Groundwater Flow near the Pumping Well, Journal of Groundwater Science and Engineering, 2, 1-11.
[18]	, 2013: Structural Control on Groundwater Distribution and Flow in the South of Ningxia Hui Autonomous Region, China, Journal of Groundwater Science and Engineering, 1, 1-8.
[19]	Wang Ping, Han Zhantao, Li Yasong, Chen Kang, Lv Xiaoli, Jian Ming, 2013: The Role of Groundwater Leakage through Deep Wells for the Deformation of Groundwater Flow: a Case Study in Cangzhou Area, Journal of Groundwater Science and Engineering, 1, 80-87.
[20]	Zong-jun Gao, Yong-gui Liu, 2013: Groundwater Flow Driven by Heat, Journal of Groundwater Science and Engineering, 1, 22-27.