For years, many research studies have focused on programming projects, assuming a deterministic environment and complete
task information. However, during the project performance, schedule may be subject to uncertainty which can lead to
significant modifications. This fact has led to an increasing scientific literature in the field. In this article we consider the
presence of an uncertainty of seasonal type (e.g. meteorological) that affects some of the activities that comprise the project. We
discuss how the project risk can be affected by such uncertainty, depending on the start date of the project. By means of Monte
Carlo simulation, we compute the statistical distribution functions of project duration at the end of the project. Then, we
represent the variability of the project through the so-called Project Risk Baseline.
In addition, we examine various sensitivity metrics - Criticality, Cruciality, Schedule Sensitivity Index -. We use them to
prioritize each one of the activities of the project depending on its start date. In the last part of the study we demonstrate the
relative importance of project tasks must consider a combined version of these three sensitivity measures.
