Title

Hbgc123D: A High-Performance Computer Model Of Coupled Hydrogeological And Biogeochemical Processes

Keywords

Bioremediation; Coupled processes; Flow and transport; Hydrobiogeochemistry; Shared-memory parallel computing

Abstract

Groundwater flow and transport models have been used to assist management of subsurface water resources and water quality. The needs of more efficient use of technical and financial resources have recently motivated the development of more effective remediation techniques and complex models of coupled hydrogeological and biogeochemical processes. We present a high-performance computer model of the coupled processes, HBGC123D. The model uses a hybrid Eulerian-Lagrangian finite element method to solve the solute transport equation and a Newton's method to solve the system of nonlinear, mixed kinetics and equilibrium reaction equations. Application of the model to a laboratory soil column with multispecies tracer injection suggests that one may use the model to derive important parameters of subsurface solute fate and transport. These parameters may be used for predictive purpose in similar field problems. To this end, we present a three-dimensional, hypothetical bioremediation simulation on an aquifer contaminated by CoNTA. The simulation suggests that, using oxygen alone to stimulate the biodegradation of the contaminant, one may reduce the waste to 40% in 10 years. Using a refined mesh of this three-dimensional model, we also conduct a performance study of HBGC123D on an array of SGI Origin 2000 distributed shared-memory processors. Both the computational kernels and the entire model show very good performance up to 32 processors. The CPU time is essentially reduced by 20-fold using 64 processors. This result suggests that HBGC123D may be a useful tool in assisting environmental restoration efforts such as waste site characterization and remediation. © 2001 Elsevier Science Ltd. All rights reserved.

Publication Date

12-1-2001

Publication Title

Computers and Geosciences

Volume

27

Issue

10

Number of Pages

1231-1242

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/S0098-3004(01)00027-9

Socpus ID

0035546539 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0035546539

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