Disaggregation of daily rainfall data using Bartlett Lewis Rectangular Pulse model: a case study in central Peninsular Malaysia

Short duration rainfall data are required for certain hydrological risk assessments. However, short timescale rainfall intensity records are still scarce due to the high cost and low reliability of the monitoring systems. One way to solve this problem is by disaggregating rainfall data using stochastic methods. This study used the Bartlett Lewis Rectangular Pulse model to disaggregate daily rainfall into hourly rainfall for ten stations in the central region of Peninsular Malaysia. The performance of the model was evaluated on its ability to reproduce statistical properties, namely the mean and standard deviation, derived from the historical records over the disaggregated rainfall. The disaggregation of daily to hourly rainfall produced daily and hourly means that closely matched the historical records. However, the standard deviations of the disaggregated daily rainfall were lower than the historical values. Despite the significant differences in the standard deviation, both data series exhibit similar patterns and the model adequately preserved the trends of all the statistical properties used in evaluating its performance.