Journal of Soil and Groundwater Environment (한국지하수토양환경학회지:지하수토양환경)

Korean Society of Soil and Groundwater Environment (한국지하수토양환경학회)
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Development of the Autoregressive and Cross-Regressive Model for Groundwater Level Prediction at Muan Coastal Aquifer in Korea

전남 무안 해안 대수층에서의 지하수위 예측을 위한 자기교차회귀모형 구축

  • Kim, Hyun Jung (Department of Earth and Environmental Sciences, Chonnam National University) ;
  • Yeo, In Wook (Department of Earth and Environmental Sciences, Chonnam National University)
  • 김현정 (전남대학교 지구환경과학부) ;
  • 여인욱 (전남대학교 지구환경과학부)
  • Received : 2014.03.17
  • Accepted : 2014.06.23
  • Published : 2014.08.31
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Abstract

Coastal aquifer in Muan, Jeonnam, has experienced heavy seawater intrusion caused by the extraction of a substantial amount of groundwater for the agricultural purpose throughout the year. It was observed that groundwater level dropped below sea level due to heavy pumping during a dry season, which could accelerate seawater intrusion. Therefore, water level needs to be monitored and managed to prevent further seawater intrusion. The purpose of this study is to develop the autoregressive-cross-regressive (ARCR) models that can predict the present or future groundwater level using its own previous values and pumping events. The ARCR model with pumping and water level data of the proceeding five hours (i.e., the model order of five) predicted groundwater level better than that of the model orders of ten and twenty. This was contrary to expectation that higher orders do increase the coefficient of determination ($R^2$) as a measure of the model's goodness. It was found that the ARCR model with order five was found to make a good prediction of next 48 hour groundwater levels after the start of pumping with $R^2$ higher than 0.9.

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References

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