Numerical modeling of geothermal groundwater flow in karst aquifer system in eastern Weibei, Shaanxi Province, China

The quantitative assessment of geothermal water resources is important to the exploitation and utilization of geothermal resources. In the geothermal water systems the density of groundwater changes with the temperature, therefore the variations in hydraulic heads and temperatures are very complicat...

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Bibliographic Details
Published in:Science China. Earth sciences 2007-06, Vol.50 (1), p.36-41
Main Authors: Li, Ming, Li, GuoMin, Yang, Liao, Dang, XueYa, Zhao, ChunHu, Hou, GuangCai, Zhang, MaoSheng
Format: Article
Language:English
Subjects:
Aquifer systems
Aquifers
China
Computer simulation
Density
Exploitation
Faults
Flow distribution
Flow pattern
Geothermal
Geothermal resources
Groundwater
Groundwater data
Groundwater dating
Groundwater flow
Heat transport
Hydrology
Karst
Mathematical models
Modelling
Numerical models
Simulation
Temperature
Three dimensional models
Water flow
Water resources
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Summary:The quantitative assessment of geothermal water resources is important to the exploitation and utilization of geothermal resources. In the geothermal water systems the density of groundwater changes with the temperature, therefore the variations in hydraulic heads and temperatures are very complicated. A three-dimensional density-dependent model coupling the groundwater flow and heat transport is established and used to simulate the geothermal water flow in the karst aquifers in eastern Weibei, Shaanxi Province, China. The multilayered karst aquifer system in the study area is cut by some major faults which control the regional groundwater flow. In order to calibrate and simulate the effect of the major faults, each fault is discretized as a belt of elements with special hydrological parameters in the numerical model. The groundwater dating data are used to be integrated with the groundwater flow pattern and calibrate the model. Simulation results show that the calculated hydraulic heads and temperature fit with the observed data well.
ISSN:1006-9313
1674-7313
1862-2801
1869-1897
DOI:10.1007/s11430-007-5020-7