Coastal areas have great significance for human living, economy and society development in the world. With the rapid increase of pressures from human activities and climate change, the safety of groundwater resource is under the threat of seawater intrusion in coastal areas. The area of Laizhou Bay is one of the most serious seawater intruded areas in China, since seawater intrusion phenomenon was firstly recognized in the middle of 1970s. This study assessed the pollution risk of a groundwater source filed of western Laizhou Bay area by inferring the probability distribution of groundwater Cl− concentration.
The numerical model of seawater intrusion process is built by using SEAWAT4. The parameter uncertainty of this model is evaluated by Markov Chain Monte Carlo (MCMC) simulation, and DREAM(ZS) is used as sampling algorithm. Then, the predictive distribution of Cl- concentration at groundwater source field is inferred by using the samples of model parameters obtained from MCMC. After that, the pollution risk of groundwater source filed is assessed by the predictive quantiles of Cl- concentration.
The results of model calibration and verification demonstrate that the DREAM(ZS) based MCMC is efficient and reliable to estimate model parameters under current observation. Under the condition of 95% confidence level, the groundwater source point will not be polluted by seawater intrusion in future five years (2015–2019). In addition, the 2.5% and 97.5% predictive quantiles show that the Cl− concentration of groundwater source field always vary between 175 mg/l and 200 mg/l.