No abstract

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.

Flooding is the main disaster type in Taiwan and is usually caused by typhoons and heavy rainfall. To understand the flood impacts in Taiwan caused by increasing rainfall due to global warming, this study adopts a high-resolution atmospheric model (HiRAM) under the representative concentration pathway (RCP) 8.5 scenario to project future changes in flood impact. For the flood simulation, the SOBEK flood model was used to determine the maximum accumulated flooding depth and flood probability in the two periods of the present and the middle of the 21st century. Yilan County, one of the most flood-prone areas in Taiwan, was chosen as a demonstration case for the development of flood impact maps. According to the results of flood map application, flooded areas were predicted to increase in the middle period of the 21st century due to increasing rainfall, especially in paddy fields, maricultural farms, and stock farms. From the base period to the middle of the 21st century, the area of flooding impacts was projected to increase from 24% to 40% in paddy fields, from 9% to 15% in maricultural farms, and from less than 1% to 9% in stock farms. These results show that the development of flood maps can help elucidate the actual impacts of climate change in Taiwan and serve as a scientific basis for adaptation actions.

<p>According to the records, an average of 5.3 typhoons hit Taiwan each year over last decade. Typhoon Morakot in 2009 was considered the most severe typhoon, which caused huge damage in Taiwan, including 677 casualty and roughly NT$ 110 billion ($3.3 billion USD) in economic loss. More and more researches documented that typhoon intensity will increase with climate change in western North Pacific region. It will induce the more severe natural disasters, such as flooding, landslide, and water resources risks in Taiwan in the future. Most research focused on the disaster impact assessment in climate change and was assumed that the land use are unchanged in the future. On the other hand, land use changes is another key reason for increasing the hazard risks. Therefore, this study tries to build a land use change model to simulate the land use spatial distribution, and discuss whether the extreme precipitation or the land use change is the major factor to increase flooding risks in Taoyuan City, northern Taiwan in the future.</p><p>This study applied that Markov chain to project the land use demand in 2036 and used the binary logits regression to establish the land use change probability model to allocate the land use spatial distribution in the future. Then, there are two different precipitation intensities used and integrated the allocated land use to evaluate the risks of flooding in 2036.</p><p>We successfully established land use spatial allocation model, and linked the allocated results to disaster impact assessment. Assessment results showed that land use change slightly increases the flooding risks; but extreme precipitation induces more severe flooding risks than land use change. Our results point out that extreme precipitation will induce the more severe flooding risks than land use. In addition, the restricted land development policy could efficiently reduce the flooding risks. If government implement climate change adaptation activities with land use management policies at the same time would possibly reduce the climate change disaster impact in the future.</p>