經驗動態建模於雨量時間序列模擬

Empirical dynamic modeling of rainfall simulation

10.6937/TWC.202203_70(1).0004

林軒德(HSUAN-TE LIN)；胡明哲(MING-CHE HU)；童慶斌(CHING-PIN TUNG)

經驗動態建模 ； 標準化降雨指標 ； 乾旱預警 ； Empirical dynamic modeling ； Standard precipitation index ； Drought warning

台灣水利

70卷1期（2022 / 03 / 01）

46 - 55

繁體中文

台灣降雨時空分配不均，豐枯水期降雨量差距大，當枯水期降雨不足，會導致水資源缺乏而無法滿足供水量。近年來，受到氣候變遷影響下，旱澇事件更加頻繁地交替發生，豐枯水期水量差距也更為懸殊，又因為工業與民生需水量上升而產生供水缺口。為了填補氣候變遷下缺水風險的增加，勢必要訂定對應的調適策略，然而興建新興水源不易，因其所投資的經濟與時間成本過高。但若能及早掌握未來降雨情境，以進行水資源調配及管理，並提供乾旱預警系統，將能有效強化水資源系統之調適能力並減少乾旱風險。故本研究目的將建構雨量時間序列模擬之經驗動態建模（Empirical Dynamic Modeling，EDM）－Simplex projection & S-map預測方法，結合標準化降雨指標（SPI），分析未來水資源之供需情勢，作為乾旱預警之用。本研究建構之Simplex projection & S-map雨量預報結合月尺度SPI-1及旬尺度SPI-1預報，結果能有效預測缺水事件，可作為乾旱預警系統的預報方法，以提供決策者及早進行水資源的調配。

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.

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