Assessment of climate change impacts on rainfall series in Peninsular Malaysia using statistical methods

There is growing interest in quantifying the impact of climate change on extreme hydrologic events where failing to integrate the effect of climate change in rainfall estimation will underestimate the severity of the events and the adequacy of current hydraulic structure designs. The purpose of this study aims is to assess the rainfall trend and frequency analysis with impact from climate change in Peninsular Malaysia using statistical methods. The thesis consists of two sections, where the statistics of rainfall trend are assessed by Mann-Kendall (MK) test and non-stationary tests while the frequency analysis illustrates the changes in distribution functions that fit full series and sub-series of annual maximum rainfall. The study area is delineated into five regions according to their distance to the nearest coast (the different extents of the influence of monsoon to the study area) to examine the spatial characteristic of the rainfall series. The MK test has detected changes for each delineated region during different monsoon seasons. At the same time, the result of non-stationary tests reveal that changes in rainfall trend have developed around year 1995 in most of the stations (41% to 50% annual rainfall over the west coast regions; more than 50% of the short duration annual maximum rainfall in the central west region have shown non-stationarity). Among the regions, the short duration rainfall in central west region show most significant increasing trend by both the MK test and the non-stationary tests. Thus, year 1995 served as trend change-point to split full series data into two sub-series data and frequency analyses are performed on these data sets. From the outcomes of the frequency analysis using two sub-series data sets, the estimated quantiles from most of the regions have increased when the sub-series posterior to 1995 is used compared to full series data, implying an overall upward rainfall trend. The results also indicate that the combination of Generalised Extreme Value distribution function and L-moments for parameters estimation (GEV-LM) outperforms the other choices. The GEV-LM is able to fit well to all regions for short-duration rainfall and three regions for long-duration rainfall. This study demonstrates the importance of incorporating climate change in rainfall assessment. There are two-fold implications of this study. First, there is considerable variability of rainfall patterns due to climate change and hence, it is important to divide the study area into regions based on the results of the MK trend and non-stationary tests. Then, the best fitted distribution function and parameter estimation method combination for frequency analysis should be tested for every region. Second, it is important to appreciate the non-stationarity of rainfall series due to climate change and the impact on how frequency analysis shall be carried out. As the warming trends in Peninsular Malaysia started around year 1995, rainfall series have shown significance upward trend, while the results of the frequency analysis (estimated quantiles) reflects the changes in the rainfall characteristics as well. Hence, in this case, it is important to concern the non-stationarity in data to achieve better estimation performance using frequency analysis.