Temporal downscaling of daily precipitation to 10 min data for assessment of climate change impact on floods in small-size watersheds applied to Jinju, South Korea

Abstract

The earth system model (ESM) mostly provides an output of hydrological variables at a daily scale, such as precipitation. Finer temporal scale data of precipitation is required for assessing the impact of climate change on floods, especially in small-size urban and mountainous watersheds which are vulnerable to floods. This study enhanced population-based nonparametric temporal downscaling (PNTD) to downscale daily precipitation to 10-min precipitation (P10M), and tested it in the Jinju area, South Korea, that includes both urban and mountainous areas. Results indicated that the enhanced PNTD model reproduced the key statistics of the P10M data and the statistical characteristics of extreme events represented by the annual maximum precipitation (AMP) series of different durations. Also, the daily precipitation of 19 ESMs with the base and future scenarios, called shared socio-economic pathways, for 245 and 585 conditions were applied and downscaled to P10M data. It was found that the future P10M precipitation scenarios were downscaled satisfactorily by preserving the difference between base and future scenarios of the AMP data. Also, results showed that the uncertainty from ESMs was about 10 times larger than from temporal downscaling and it indicated that the uncertainty in temporal downscaling can be acceptable. The P10M data can be employed for deriving intensity-duration-frequency curves needed for designing urban drainage systems and other hydraulic and hydrologic structures and for installing flood warning systems.