Projected Changes of Precipitation IDF Curves for Short Duration under Climate Change in Central Vietnam

Abstract

Abstract:In future years, extreme weather events are expected to frequently increase due to climate change, especially in the combination of climate change and events of El Niño-Southern Oscillation. This pays special attention to the construction of intensity-duration-frequency (IDF) curves at a tempo-spatial scale of sub-daily and sub-grid under a context of climate change. The reason for this is that IDF curves represent essential means to study effects on the performance of drainage systems, damps, dikes and reservoirs. Therefore, the objective of this study is to present an approach to construct future IDF curves with high temporo-spatial resolutions under climate change in central Vietnam, using the case of VuGia-ThuBon. The climate data of historical and future from a regional climate model RegCM4 forced by three global models MPI-ESM-MR, IPSL-CM5A-LR and ICHEC-EC-EARTH are used to re-grid the resolution of 10 km × 10 km grid spacing from 25 km × 25 km on the base of bilinear interpolation. A bias correction method is then applied to the finest resolution of a hydrostatic climate model for an ensemble of simulations. Furthermore, the IDF curves for short durations of precipitation are constructed for the historical climate and future climates under two representative concentration pathway (RCP) scenarios, RCP4.5 and RCP8.5, based on terms of correlation factors. The major findings show that the projected precipitation changes are expected to significantly increase by about 10 to 30% under the scenarios of RCP4.5 and RCP8.5. The projected changes of a maximum of 1-, 2-, and 3-days precipitation are expected to increase by about 30-300 mm/day. More importantly, for all return periods (i.e., 10, 20, 50, 100, and 200 years), IDF curves completely constructed for short durations of precipitation at sub-daily show an increase in intensities for the RCP4.5 and RCP8.5 scenarios.

Projections of Future Climate Change in the Vu Gia Thu Bon River Basin, Vietnam by Using Statistical DownScaling Model (SDSM)

“…Particularly, the greatest increasing trends in annual rainfall at Hien station are estimated by 26.9%-31.3% for the 2080s under the worst-case scenarios (HadCM3 A2 and CanESM2 RCP8.5). It is worth noting that several previous studies [33,34] indicated increasing trends in annual rainfall over the VGTB river basin by applying bias correction approaches, which differs from those found in the present study. To a certain extent, these findings reflect various uncertainties in future projections of daily rainfall.…”

“…It is discernible that most previous investigations employed dynamical downscaling approach by applying Conformal Cubic Atmospheric Model (CCAM), Regional Climate Model Version 3 (RegCM3), Regional Model (REMO), and PRECIS models. In the Vu Gia Thu Bon (VGTB) river basin, Thanh and Dutto [33], Nam et al [34] employed a number of bias correction techniques to reduce systematic biases from the outputs of multiple GCMs/RCMs, which were subsequently used to assess the impacts of climate change on extreme flood events.…”

Monitoring Land Surface Temperature Change with Landsat Images during Dry Seasons in Bac Binh, Vietnam

“…Climate change, along with urbanization, causes severe impacts in Vietnam, like the intensification and durations of floods and droughts. These heat-related changes put ecosystems under stress and affect the wellbeing of the local population with extreme heat events [2][3][4][5][6].…”

Xây dựng đường cong cường độ–thời đoạn–tần suất mưa hướng đến thiết lập bản đồ ngập lụt cho khu vực bán đảo Cà Mau

“…Nhóm nghiên cứu đã báo cáo rằng phương pháp tính toán tần suất lũ thiết kế dựa trên đường cong IDF mưa là phù hợp và triển vọng áp dụng cho những khu vực khác của Việt Nam. Gây đây, năm 2018 [14] đã tiến hành một nghiên cứu xây dựng đường cong IDF mưa cho khu vực sông Vu Gia-Thu Bồn trong bối cảnh BĐKH, dựa trên chuỗi dữ liệu mưa ngày. Để tiến hành nghiên cứu này, nhóm tác giả đã sử dụng dữ liệu mưa lịch sử từ mô hình RegCM4 theo kịch bản RCP4.5 và RCP8.5 với độ phân giải lưới 10km x 10km.…”