ABSTRACT

Based on the monitoring data of two seawater intrusion sections from 2010 to 2018, the development trend of seawater intrusion in eastern coast of Laizhou Bay was analyzed. The results showed that groundwater chlorinity had an obvious negative correlation with precipitation and an obvious positive correlation with groundwater exploitation. The artificial neural network (ANN) was used to establish the relationship between precipitation, groundwater exploitation, groundwater chlorinity and groundwater level. The control standard of groundwater in eastern coast of Laizhou Bay was obtained. The research results provide a theoretical basis for seawater intrusion prevention and resource utilization of coastal area.

INTRODUCTION

Laizhou Bay is the most serious and typical area of seawater intrusion in China. The seawater intrusion in Laizhou Bay began in the late 1970s, due to the rapid development of economy and the impact of human factors on the environment. (Wei,2010) The area of seawater intrusion in Laizhou Bay has developed from 1692 km2 in 1980 to 4300 km2 in 2010. (Chen,2013) Seawater intrusion disasters pollute the underground fresh water resources, resulting in the deterioration of the ecological environment, which has a serious impact on coastal areas.

The development of seawater intrusion in Laizhou Bay area involves many factors, such as hydrogeological environment, topographic and geomorphic characteristics, climate and human activities. While hydrogeological environment and topographic and geomorphic characteristics are the basic factors for the occurrence of seawater intrusion. Human activity is the inducing factor.

In order to control seawater intrusion, the most effective measure is to reduce the exploitation of underground fresh water and balance the interface of seawater and fresh water.

In this paper, based on the monitoring data of two seawater intrusion sections in eastern coast of Laizhou Bay from 2010 to 2018, the development trend of seawater intrusion was analyzed. The artificial neural network (ANN) was used to establish the relationship between precipitation, groundwater exploitation, groundwater chlorinity and groundwater level. The double control standard of groundwater (groundwater level and groundwater exploitation) with no seawater intrusion was obtained. The research results provide a theoretical basis for seawater intrusion prevention and resource utilization of coastal area.

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