The management of coastal aquifers requires careful planning of withdrawal strategies for control and remediation of saltwater intrusion. Over exploitation of groundwater in coastal aquifers may result in intrusion of saltwater. Prediction and control of future saltwater distribution in coastal aquifer may be possible by simulating the processes with utilizing mathematical models. The groundwater resources in North Sinai area are affected by salt water up-coming due to over-pumping phenomenon beside seawater intrusion. The objective of this study was to apply mathematical modeling techniques for water resource management in salt-affected ecosystems. The study area is located in the northern coastal zone of Sinai Peninsula of Egypt and covers about 1750 km(2). The methodological approach to simulate the groundwater flow is based on the mathematical modeling techniques with applying 3-D finite element software (FEFLOW model). Three management scenarios are applied to predict the drawdown of groundwater levels under different extraction rates and seawater intrusion phenomenon. In addition, the methodology of seawater intrusion study and calibration was based on applying two-dimensional finite element simulation (SWI) code. The results of ground-water flow simulation show optimum groundwater extractions 26 x 10(6) m(3)/year from the cultivated areas. Moreover, simulation results indicate that the seawater/freshwater interface will migrate, after 15 years, at the distance of 5.5 km landward from its initial position if the present groundwater production policy (19 x 10(6) m(3)/year) continues operating in the area. To conserve the Quaternary Aquifer in North Sinai coastal Area (QANSA) storage for longer time, it is recommended to reduce the number of the pumping wells (<300 wells) as well as the initial and running time (does not exceed 10 h), and to achieve the objective of implementing the developing policy without any increase (500 m(3)/day/well). It is highly recommended to carry out geophysical exploration study and to construct monitoring network to verify the results of the applied model.