Multivariate approaches optimize locations of groundwater pumping facilities for different hydrogeological scales

Hydrological Processes

Volumn 26, Issue 19, 2012, Pages 2985-2996

  Lin, Hsien Tsung ^a   Tan, Yih Chi ^a   Chen, Chu Hui ^b   Lin, Wen Sheng ^a   Liu, Chen Wuing ^a  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^b CHINA UNIVERSITY OF TECHNOLOGY   (Taiwan)

Author keywords

Artificial neural networks; Hydraulic conductivities; Hydrogeological scale; Pumping test

Indexed keywords

ARTIFICIAL NEURAL NETWORK APPROACH; CALIBRATION AND VERIFICATION; ESTIMATION PARAMETERS; GROUNDWATER PUMPING; HETEROGENEOUS POROUS MEDIA; HYDROGEOLOGICAL; LOCAL SCALE; MULTIVARIATE APPROACH; OBSERVATION WELLS; OPTIMIZATION APPROACH; PUMPING TESTS; RECHARGE AREA; REGIONAL SCALE; SAFE YIELDS; SPATIAL DIRECTION; STUDY AREAS; WELL GROUP;

AQUIFERS; COMPUTER SIMULATION; GROUNDWATER RESOURCES; HYDRAULIC CONDUCTIVITY; NEURAL NETWORKS; OPTIMIZATION; POROUS MATERIALS; PUMPS;

RECHARGING (UNDERGROUND WATERS);

ARTIFICIAL NEURAL NETWORK; GROUNDWATER; HYDRAULIC CONDUCTIVITY; HYDROGEOLOGY; MULTIVARIATE ANALYSIS; NUMERICAL MODEL; OPTIMIZATION; POROUS MEDIUM; PUMPING; RECHARGE;

EID: 84865341296     PISSN: 08856087     EISSN: 10991085     Source Type: Journal    
DOI: 10.1002/hyp.8307     Document Type: Article

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