The ability of sensitivity techniques developed at the Center for Nuclear Waste Regulatory Analyses (CNWRA) to highlight non-monotonic trends is studied in this paper. The capability of the parameter tree, the mean-based and standard deviation-based sensitivity, and the partitioning methods to identify sensitivities of non-monotonic functions is explored. Sensitivity indices and significance tests for the various techniques are discussed in the paper. It is concluded that the standard deviation-based index can consistently identify non-monotonic trends. The parameter tree and the partitioning methods provide some capability to detect non-monotonic trends; however, they lack resolution if the performance metric reaches a maximum...