The Impact of Climate Change on Rainfall Erosivity in Taiwan
Date Issued
2006
Date
2006
Author(s)
Yang, Wen-Jen
DOI
zh-TW
Abstract
ABSTRACT
In this study, the rainfall data were collected from Central Weather Bureau and Water Resource Agency in Taiwan. Using these data, the CLIGEN model was validated for Taiwan based upon the attributes of historical rainfall events from the analysis results. The impact of climate change on rainfall erosivity (the R factor) in Taiwan was assessed as well.
Results show that the effective rainfall in Taiwan was more than 80% of the mean annual rainfall. The distribution types of the maximum 30-minute rainfall intensity (I30) in southwest and northeast area were leptokurtosis and platykurtosis respectivily, and there was a good relationship between I30 and mean rainfall intensity. According to the analysis results of effective rainfall events, a regession model and a Back-Propagation artifical neurual network (BPN) were established, and the BPN has a better performance in predicting the I30. Apart from these, the CLIGEN weather generator was found to be satisfactory in modeling the annual precipitation and monthly precipitation in Taiwan. However, further validation for the other important attributes of effective rainfall events was required.
The simulation results of the GISS equilibrium experiment show that the annual rainfall erosivity tends to increase in Keelung, Ilan, Hsinchu, Chiayi and Hualien, and decrease in Kaoshiun and Taidong under the scenario of 2 times concentration of CO2. From the results of HADCM3 transition experiment, it was found that future climate change might have significant influence on rainfall erosivity in Taiwan. Except for B2 scenario, there was an increasing trendency for the R factor during the short, medium and long term, southwest area in long term especially. The increase in the R factor will lead to increase the soil erosion as well, if other factors in the Revised Universal Soil Loss Equation (RUSLE) remain constant. However, the assumption doesn’t consider that the influence of climate change on the factor C, the research for the impact of climate change on soil erosion needs to be further studied.
Subjects
氣候變遷
降雨沖蝕指數
最大三十分鐘降雨強度
氣候生成模式
類神經網路
全球暖化
Climate change
Rainfall erosivity
The maximum 30-minute rainfall intensity
Climate generator
Artifical neurual network
Global warming
SDGs
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-95-D92622001-1.pdf
Size
23.53 KB
Format
Adobe PDF
Checksum
(MD5):03741b3786fee04632abcdc7b51ed7f9