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SUMMARY:Application of Neural Network Model to Predict and to Evaluate the
  Groundwater Level Fluctuation
DTSTART;VALUE=DATE-TIME:20191108T072500Z
DTEND;VALUE=DATE-TIME:20191108T074000Z
DTSTAMP;VALUE=DATE-TIME:20260724T092828Z
UID:indico-contribution-17@sshep.snu.ac.kr
DESCRIPTION:Speakers: Sanghoon Lee (Seoul National University)\nGroundwate
 r is one of valuable water resources used for the various purposes in our 
 life\, but it is not limitless. For this reason\, prediction and managemen
 t of the groundwater are very essential work for sustainable use of it. Ph
 ysics-based models are usually applied on prediction of groundwater level\
 , but they are hard to be implemented successfully when there is any unkno
 wn physical property or when subterranean structure is very complicated. I
 n this research\, prediction of the groundwater level at riverside area in
  Yangpyeong\, Korea was carried out using neural network model instead. In
  study area where several natural and anthropogenic factors affect the gro
 undwater level fluctuation\, groundwater levels at 8 monitoring wells were
  well predicted with low range of RMSE errors. Moreover\, monthly contribu
 tions\, which indicate the impact of input variables\, were computed to fi
 gure out the seasonal variance of influencing factors. This study could su
 ggest another option to predict the groundwater level\, and help understan
 ding spatial and temporal variation of impacts of factors affecting the gr
 oundwater level fluctuation.\n\nAcknowledgement: This work was supported b
 y the National Research Foundation of Korea(NRF) grant funded by the Korea
  government(MSIP) (No. 2017R1A2B3002119)\n\nhttps://sshep.snu.ac.kr/event/
 107/contributions/17/
LOCATION:Seoul National University\, College of Natural Sciences\, Buildin
 g 25-1 국제회의실 (International Conference Hall)
URL:https://sshep.snu.ac.kr/event/107/contributions/17/
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