Coastal development affects human life and economic activity. Given a necessity to develop coastal areas, there is a need for a method by which to understand and quantitatively assess and predict changes to coastal marine environments. In this paper, we propose a mathematical modeling for coastal marine environments using observational data. In particular, we establish probabilistic graphical model based on the data-driven statistical model for Saemangeum coast of Korea, where land reclamation work has been taking place. The derived model consists of latent and observation variables and their causal relationships. Ocean currents occurred by water exchange appear to be the key factor influencing the coastal marine environments in the artificial lake of Saemangeum coast. Hence, coastal water quality in the coastal management is the major concern by stakeholders. Using the proposed model we were able to compute the followings to demonstrate the usage of our proposed model: First, if the lake were to be entirely cut off from sea water exchange (which takes place through sluice gates in the sea dyke to the open sea), coastal water quality may deteriorated to approximately 37.5% of its current quality. Secondly, in order to maintain a minimum acceptable coastal water quality in the artificial lake, permitting its use in industrial supply and agriculture, currents of about 0.6 m/s are required for sea water exchange. This approach will assist in coastal management by supporting decision-making, policy planning, and the establishment of strategies for sustainable coastal development and conservation of coastal marine environments.