A downscaling-disaggregation approach for developing IDF curves in arid regions

Over the past decades, urbanization in Arabian Gulf region expands in flood-prone areas at an unprecedented rate. Chronic water stress and potential changes in extreme rainfall attributed to climate change therefore pose unique challenges in planning and designing water management infrastructures. The objective of this study is to develop a framework to integrate climate change variations into intensity-duration-frequency (IDF) curves in Oman. A two-stage downscaling-disaggregation method was applied with rainfall at Tawi-Atair station in Dhofar region. Potential variations of extreme rainfall in future were examined by eight scenarios composed with two general circulation models (GCMs), two representative concentration pathways (RCPs), and two future periods (2040-2059 and 2080-2099). A stochastic weather generator model was used to downscale rainfall output from GCM grid scale to local scale. Downscaled daily data were then disaggregated to hourly and 5-min series by using K-nearest neighbor (K-NN) technique. Annual maximum rainfall extracted from eight future scenarios and also from present climate (baseline period) was used to develop rainfall intensity-frequency relationships for eight durations range from 5 min to 24 h. Results of the K-NN analysis indicate that the optimum window size of 57 days and 181 h is suitable for hourly and 5-min disaggregation models, respectively. Results also predict that the effects of climate change on the rainfall intensity will be more significant on storms with shorter durations and higher return periods. Moving towards the end of the twenty-first century, the return period of extreme rainfall events is likely to decrease due to intensified rainfall events.