This paper reviews optimization models in the context of water resources management and security. The article is instituted on four fundamental pillars: (a) an understanding of the quantum of key optimization techniques adopted by the researchers over the past few decades in managing water resources, (b) an enumeration of these techniques, both in terms of their brief mathematical structures and with reference to their representative applications in managing water resources so as to conform to one of the four perspectives of water security, viz. welfare, equity, sustainability, and risk, (c) an evaluation of major challenges associated with these conventional equation-based optimization techniques, including the perceptive account of the distinction between the gradient-based local optimization and non-gradient global optimization, and finally, (d) an assessment of context-sensitive appropriateness of simulation-based bottom-up modeling schemes, with special reference to evolutionary algorithms. The review emphasizes that the ontology of conventional equation-based models lies in an aggregate manifestation of social behavior and, as a result, it fails to capture individuals’ behaviors juxtaposed with ecological and hydrological systems while modeling complex water resources. On the contrary, the expediency of the domain of operational research in responding to societal problems ensuing from a scarce natural resource like water lies in bottom-up optimization schemes, which are more obliging in the sense that they can incarcerate such social explanations in the modeling frame based on local values.