Abstract
To understand the characteristics of severe floods under global climate change, we created a design hyetograph for a 100-year return period. This incorporates a modified ranking method using the top 10 extreme rainfall events for present, near-future, and far-future periods. The rainfall data sets were projected with a general circulation model with high spatial and temporal resolution and used with a flood model to simulate the higher discharge peaks for the top 10 events of each term in a local watershed. The conventional-like ranking method, in which only a dimensionless shape is considered for the creation of a design hyetograph for a temporal distribution of rainfall, likely results in overestimates of discharge peaks because, even with a lower peak of rainfall intensity and a smaller amount of cumulative rainfall, the distribution shape is the only the factor for the design hyetograph. However, the modified ranking method, which considers amounts of cumulative rainfalls, provides a discharge peak from the design hyetograph less affected by a smaller cumulative rainfall depth for extreme rainfall. Furthermore, the effects of global climate change indicate that future discharge peaks will increase by up to three times of those of Present-term peaks, which may result in difficult flood control for the downstream river reaches.
Highlights
IntroductionClimate change is likely to have caused numerous occurrences of extreme weather (e.g., severe tropical cyclones and monsoon rainfalls in East Asia) over the last decade and may continue to induce frequent occurrences of extreme weather until the end of the 21st century [1,2]
Climate change is likely to have caused numerous occurrences of extreme weather over the last decade and may continue to induce frequent occurrences of extreme weather until the end of the 21st century [1,2]
Being interested in estimates of the largest discharge that may cause severe flood-induced damage during extreme weather, we focused on the generation of a design hyetograph with high intensity, which can represent extreme rainfall events obtained from the MRI-Weather Research and Forecasting (WRF) data
Summary
Climate change is likely to have caused numerous occurrences of extreme weather (e.g., severe tropical cyclones and monsoon rainfalls in East Asia) over the last decade and may continue to induce frequent occurrences of extreme weather until the end of the 21st century [1,2]. Severe floods and debris flows have occurred often in Taiwan during the last decade [3]. To simulate the highest discharge peak that may occur under global climate change in Taiwan, we focused on two improvements: a detailed data set with higher temporal and spatial resolutions and a better method of representing the artificial temporal distribution of rainfall (a design hyetograph). In Taiwan a 24-h temporal distribution has been employed with a conventional ranking method [5] with a dimensionless approach [6], which considers the shape of the rainfall distribution. The ranking method could be further improved by considering the amount of cumulative rainfall depth as well as the shape of the temporal distribution for an extreme rainfall event. Extending the period of the design hyetograph was considered based on data from recent typhoons [9], which brought large amounts of rainfall beyond the 24-h period
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