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Time Series Analysis and Forecasting of Electrical Conductivity in Coastal Aquifers

연안암반대수층의 해수침투경향성 파악을 위한 전기전도도 시계열 분석과 예측

  • Received : 2017.08.08
  • Accepted : 2017.08.28
  • Published : 2017.08.28

Abstract

Seawater intrusion into coastal fractured rock aquifer, resulting in groundwater contamination, is of serious concern in coastal areas of Jeolla Namdo, Korea, which heavily depends on groundwater resources. Time series analysis and forecasting were carried out to analyze and predict EC which is a major indicator of seawater intrusion. Two time series models of autoregressive integrated moving average (ARIMA) and seasonal autoregressive integrated moving average (SARIMA) were tested for suggesting appropriate time series model. Time series data of EC measured over one year showed a increasing trend with short periodic fluctuations, due to tidal effect and pumping, which indicated that EC time series data tended to be non-stationary. SARIMA model was found better fitted to observed EC than any other time series model. Time series analysis and modeling was found to be a useful tool to analyze EC at coastal fractured rock aquifer subject to seawater intrusion.

전라남도는 연안지역은 농업활동과 상수도의 미보급으로 인하여 지하수에 크게 의존하고 있다. 지하수의 과다사용은 지하수위 저하를 일으키며 그로 인한 해수침투가 발생할 가능성이 매우 높다. 따라서 지하수 사용에 따른 해수침투 관리가 매우 필요한 지역이다. 전라남도 무안군의 연안암반대수층에서 측정된 EC 자료를 이용하여 해안가 대수층에 적합한 시계열 모형을 구축하고, 해수침투의 지표인 EC를 예측하고자 시계열 분석을 수행하였다. 1년 이상 측정한 EC 시계열 자료는 짧은 주기적인 변동과 함께 추세적으로 증가하는 비정상 시계열의 특성을 보였다. 시계열 분석을 통해 시계열 모형 식별 결과 ARIMA 모형과 계절적인 요인을 고려 할 수 있는 SARIMA 모형 이 적합한 것으로 나타났다. 하지만 두 모형 적용한 결과, EC의 주기적인 변동으로 인해 ARIMA보다는 EC 자료의 변동 특성을 잘 반영한 SARIMA 모형이 예측에 있어서 유리한 것으로 나타났다. 위와 같이 시계열 분석은 암반 대수층에서 해수침투로 인한 EC의 변화를 예측하는데 있어 유용한 것으로 나타났다.

Keywords

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