A Cost-Risk Weather Index Framework for Scheduling Nuclear Site Preparation in Tropical Climates

Nuclear Power Plant (NPP) site preparation in tropical regions faces significant schedule and cost risks due to rainfall, which are often addressed with inadequate and unspecified contingencies. This study develops an integrated framework to address these issues by converting multi-year daily rainfall data into auditable seasonal risk inputs for project simulations. The methodology involves synthesizing rainfall data from multiple stations with quality weighting, mapping rainfall to Lost Time Hours (LTH) using a double logistic function, and applying time–cost co-sampling analysis in Primavera Risk Analysis. Applied to the Indonesian case study, the framework predicts an increase in P80 duration of 36 days, or 10.17%, and an increase in cost of USD 64,809, or 8.41%. This analysis reveals that the raw rainfall index is only weakly correlated with delays and cost overruns at the project level, because the network structure and monthly usage levels filter out the weather signal; this weak correlation and the systematic time–cost decoupling encourage comprehensive network simulations rather than simply accounting for uniform weather allowances. This methodology has potential applications for site preparation activities and other types of infrastructure. However, validation on external datasets and calibration to local climate and operational contexts remain critical future steps. This framework provides a transparent and replicable approach to converting local climate data into project-specific contingency data, improving schedule reliability and cost control for construction projects in tropical regions.