Due to random behavior of flood events and inaccuracies in measurements, design, analysis, and operation of flood control systems are subjected to several uncertainties. An important aspect in developing stochastic models for evaluating and analyzing more than one uncertainty is the dependence or independence of them. In flood control projects, hydrologic, hydraulic, geotechnical, and economic uncertainties are important considerations. In this paper, a stochastic Monte-Carlo simulation – optimization modeling approach is described for risk-based design of flood control levees (as a common structural flood control measure): considering multiple dependent uncertainties. It has been applied to the Leaf River reach in Hattiesburg, Mississippi for testing and evaluation of modeling results. Unlike a deterministic model that yields just one set of values for system dimensions, the stochastic model solution gives a range of values for each of them. One of the major reasons for limited field application of uncertainty analysis is difficulties in performing the modeling results in real world contexts. For closing the gap between theory and reality, design charts are developed in this study. This helps decision makers in identifying design values with desired and accepted risks.