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A robust method to develop future rainfall IDF curves under climate change condition in two major basins of Iran.
- Source :
- Theoretical & Applied Climatology; Apr2021, Vol. 144 Issue 1/2, p179-190, 12p, 5 Charts, 5 Graphs, 1 Map
- Publication Year :
- 2021
-
Abstract
- Current rainfall Intensity-Duration-Frequency (IDFs) curves generally were developed based on stationary extreme value assumption. However, climate change is expected to alter extreme rainfalls and invalidate the stationary assumption. So, it is crucial to develop future rainfall IDFs taking into account the impacts of climate change. Difficulty in preparing reliable rainfall time series with fine time step and capturing extremes for future climate scenarios has led to limited studies aimed at investigating the change of IDF curves due to climate change. In this paper, a robust stochastic rainfall model (NSRP) is employed to produce future rainfall IDFs for five stations across Karkheh and Karun basins in Iran. NSRP can generate long-term realistic rainfall series containing extremes. Moreover, it applies changes in different rainfall statistical characteristics, projected by GCMs, in the downscaling procedure. For each station, the model was calibrated using observed rainfalls series. Then, 3000-year daily rainfall series were generated, and historical IDFs were developed. Consequently, NSRP parameters were perturbed based on GCM projections. Then, 3000-year future rainfall series were generated, and future IDFs were developed. The climate change uncertainties were represented by employing two GCM (CanESM2 and HadGem2) and three emission scenarios (RCP2.6, RCP4.5, and RCP8.5). The results showed NSRP is able to reproduce observed extreme rainfalls in a wide range of time scales. Also, climate change will lead to a considerable increase in future extreme rainfall intensity in the study basins. As averages of all considered scenarios, rainfall intensities will increase between 22 and 206% in the future. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 0177798X
- Volume :
- 144
- Issue :
- 1/2
- Database :
- Complementary Index
- Journal :
- Theoretical & Applied Climatology
- Publication Type :
- Academic Journal
- Accession number :
- 149398593
- Full Text :
- https://doi.org/10.1007/s00704-021-03540-0