Analysis of Extreme Rainfall Trends in Sicily for the Evaluation of Depth-Duration-Frequency Curves in Climate Change Scenarios

2015 ◽  
Vol 20 (12) ◽  
pp. 04015036 ◽  
Author(s):  
Lorena Liuzzo ◽  
Gabriele Freni
2020 ◽  
Vol 13 (1) ◽  
pp. 105
Author(s):  
Jaekyoung Kim ◽  
Junsuk Kang

The social and economic damages caused by climate change have increased rapidly over the last several decades, with increasing instances of heatwaves, floods, and extreme rainfall. In 2011, heavy rain of 110.5 mm/hr caused great damage to the Seoul Metropolitan Government. Most of the causes of flooding in modern cities include a sharp increase in non-permeable pavement and a lack of water circulation facilities. It is predicted that heavy rainfalls will occur in the future, causing large amounts of local damage. In this study, possible future flood damages were analyzed using climate change scenarios based on the Korean Peninsula. ArcGIS was adopted to perform analyses, and Huff curves were employed for precipitation analysis. Water tanks, permeable pavement, and ecological waterways were installed as mitigation technologies. These three technologies can contribute to flooding mitigation by increasing the rainwater storage capacity. This study suggests that all floods can be reduced by RCP 8.5 by 2050 and 2060. Although there will be run-off after 2050, it is believed that technology will significantly reduce the volume and possibility of floods. It is recommended that a one-year analysis should be conducted in consideration of the maintenance aspects that will arise in the future.


2019 ◽  
Vol 271 ◽  
pp. 04002 ◽  
Author(s):  
Cesar Do Lago ◽  
Eduardo Mendiondo ◽  
Francisco Olivera ◽  
Marcio Giocomoni

Potential consequences of climate change are the increase in the magnitude and frequency of extreme rainfall storm events. In order to assess what are the potential impacts of climate change in the transportation infrastructure, new intensity-duration-frequency curves are needed. In this study, projected IDF curves were created based on three Global Climate Models (GCM) for the representative concentration pathways (RCP) 4.5 and 8.5. The selected GCMs are: ACCESS1-0, CSIRO-MK3-0-6 and GFDL-ESM2M. Projected IDFs for the near (2025-2049), mid (2050-2074) and far future (2075-2099) were created after disaggregating the project rainfall time series using the Bartlett-Lewis Rectangular Pulses Stochastic Model. The projected IDFs were compared with the IDF currently used and generated based on historical data. The results indicate that climate change is likely to decrease rainfall intensities in all the future horizons in the tested area of San Antonio, Texas. Further analysis is recommended, including the use of bias correction of those GCM models and use of a broader range of models that can better quantify uncertainty of the future rainfall regime.


Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 564
Author(s):  
Yung-Ming Chen ◽  
Chi-Wen Chen ◽  
Yi-Chiung Chao ◽  
Yu-Shiang Tung ◽  
Jun-Jih Liou ◽  
...  

Affected by climate change owing to global warming, the frequency of extreme rainfall events has gradually increased in recent years. Many studies have analyzed the impacts of climate change in various fields. However, uncertainty about the scenarios they used is still an important issue. This study used two and four multi-scenarios at the base period (1979–2003) and the end of the 21st century (2075–2099) to collect the top-ranking typhoons and analyze the rainfall conditions of these typhoons in two catchments in northern Taiwan. The landslide-area characteristics caused by these typhoons were estimated using empirical relationships, with rainfall conditions established by a previous study. In addition to counting landslide-area characteristics caused by the typhoons of each single scenario, we also used the ensemble method to combine all scenarios to calculate landslide-area characteristic statistics. Comparing the statistical results of each single scenario and the ensembles, we found that the ensemble method minimized the uncertainty and identified the possible most severe case from the simulation. We further separated typhoons into the top 5%, 5%–10%, and 10%–15% to confirm possible changes in landslide-area characteristics under climate change. We noticed that the uncertainty of the base period and the end of the 21st century almost overlapped if only a single scenario was used. In contrast, the ensemble approach successfully distinguished the differences in both the average values of landslide-area characteristics and the 95% confidence intervals. The ensemble results indicated that the landslide magnitude triggered by medium- and high-level typhoons (top 5%–15%) will increase by 24%–29% and 125%–200% under climate change in the Shihmen Reservoir catchment and the Xindian River catchment, respectively, while landslides triggered by extreme-level typhoons (top 5%) will increase by 8% and 77%, respectively. Still, the uncertainty of landslide-area characteristics caused by extreme typhoon events is slightly high, indicating that we need to include more possible scenarios in future work.


2021 ◽  
Author(s):  
Myeong-Ho Yeo ◽  
Van-Thanh-Van Nguyen ◽  
Yong Sang Kim ◽  
Theodore A. Kpodonu

Abstract The estimation of the Intensity-Duration-Frequency (IDF) relations is often necessary for the planning and design of various hydraulic structures and design storms. It has been an increasingly greater challenge due to climate change condition. This paper therefore proposes an integrated extreme rainfall modeling software package (SDExtreme) for constructing the IDF relations at a local site in the context of climate change. The proposed tool is based on a temporal downscaling method to describe the relationships between daily and sub-daily extreme precipitation using the scale-invariance General Extreme Value (GEV) distribution. In addition, SDExtreme provides a modified bootstrap technique to determine confidence intervals (CIs) of the estimated IDF curves for the current and the future climate conditions. The feasibility and accuracy of SDExtreme were assessed using rainfall data available from the selected rain gauge stations in Quebec and Ontario provinces (Canada) and climate simulations under three different climate change scenarios provided by the Canadian Earth System Model (CanESM2) and the Canadian Regional Climate Model (CanRCM4).


2005 ◽  
Vol 33 (1) ◽  
pp. 185-188 ◽  
Author(s):  
Csilla Farkas ◽  
Roger Randriamampianina ◽  
Juraj Majerčak

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