https://scholars.lib.ntu.edu.tw/handle/123456789/632614
標題: | Empirical dynamic modeling of rainfall simulation | 作者: | Lin, Hsuan Te MING-CHE HU CHING-PIN TUNG |
關鍵字: | Drought warning; Empirical dynamic modeling; Standard precipitation index | 公開日期: | 1-三月-2022 | 卷: | 70 | 期: | 1 | 來源出版物: | Taiwan Water Conservancy | 摘要: | The temporal and spatial distribution of rainfall is uneven in Taiwan. There is a significant difference between cumulative rainfall in dry seasons and wet seasons. If the rainfall was insufficient in dry seasons, the water demand couldn’t be satisfied due to the lack of water resources. Due to the influence of climate change, the frequency of drought or flood events increases gradually. The rainfall difference between wet and dry seasons will be more drastic in comparison to past years. In addition, the increasing industrial and residential water demand incurs water shortage problem. It will force the government to adopt water rationing or fallow policy, which would cause a significant economic loss and inconvenience to people. To respond the increasing risk of drought under climate change, corresponding adaptation strategies must be established. However, building new reservoirs and facilities is expensive and time-consuming. If the future water shortage can be predicted, water resources management and allocation could be used to prevent the water shortage. The prediction can be also used to develop a drought early warning system as an adaptation measure, which will strengthen the adaptive capacity of the water supply system and reduce the impacts of drought events. In this research, an Empirical Dynamic Modeling (EDM) seasonal weather forecast has been developed by applying empirical dynamic modeling predicting method─Simplex projection & S-map combining with Standard Precipitation Index (SPI). The EDM seasonal weather forecast is conducted for the rainfall and drought simulation. The results of the EDM seasonal weather forecast show that the predictions by monthly SPI-1 and ten-days SPI-1 can simulate the situation of water shortage. The predictions provide drought early warning to allocate water resources at an early date for decision making. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85154065405&doi=10.6937%2fTWC.202203_70%281%29.0004&partnerID=40&md5=f1e1ad1f96426a9b112d4496f7cccf6c https://scholars.lib.ntu.edu.tw/handle/123456789/632614 |
ISSN: | 04921550 | DOI: | 10.6937/TWC.202203_70(1).0004 |
顯示於: | 生物環境系統工程學系 |
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