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《Journal of Jilin University(Earth Science Edition)》 2006-S1
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Usage of Artificial Neural Networks Technique in Karst Water Recoverable Reserve Evaluation——Give an Example of Shanxi Jinci Spring

YIN Dan(1,2),SU Xiao-si(1,2),LI Yan-ge(3),FENG Yu-ming(4) 1.Institute of Water Resources and Environment,Jilin University,Changchun 130026,China 2.College of Environment and Resources,Jilin University,Changchun 130026,China 3.Nanjing Hydraulic Research Institute,Nanjing 210029,China 4.Taiyuan Water Conservancy Bureau,Taiyuan 030002,China  
We established the ANN model between the groundwater level of Jinci spring area and the recharge and drainage of the groundwater system,based on the analysis of the area's hydrogeology condition,and then did the evaluation of this area's allowable withdraw of groundwater.The result of this study indicated that this ANN model had a high level of simulation precision;the result of the evaluation was consistent with the real exploitation and usage of this spring area.Simultaneity,this text calculate the recoverable reserve in different precipitation conditions,and make the evaluation more significance.
【Fund】: 国家重点基础研究发展规划(973)项目(G1999043606);; 吉林大学“985”计划项目;; 教育部城市环境与可持续发展联合研究中心吉林大学分中心和水资源与水环境问题重点实验室(原地质矿产部水资源评价与管理系列模型开放研究实验室)资助
【CateGory Index】: P641.8
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