Empirical dynamic modeling of rainfall simulation
Journal
Taiwan Water Conservancy
Journal Volume
70
Journal Issue
1
Date Issued
2022-03-01
Author(s)
Abstract
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.
Subjects
Drought warning; Empirical dynamic modeling; Standard precipitation index
Type
journal article