This paper proposes a novel robust optimization (RO) approach along with a two-stage scenario-based stochastic programming to optimize a municipal water distribution system (WDS) under demand and rainfall uncertainties. Firstly, we have proposed a new multi-period mixed-integer linear programming (MILP) formulation of a municipal WDS. The goal is to find solutions that are both cost-effective and completely fulfill potable and non-potable demand in an integrated system. Furthermore, a novel RO approach is developed which attempts to adjust protection level in a column what we call "adjustable column-wise robust optimization". The interesting point of the proposed RO approach is its linear structure and being computationally tractable. The efficiency of the proposed models are evaluated through a real case study of Mashhad. The acquired results reveal the proposed WDS model have dramatically reduced the total costs. Simultaneously, the RO approach has risen robustness besides realization demonstrates its better performance than deterministic one. (c) 2017 Elsevier Ltd. All rights reserved.