氣侯變遷下農業用水對區域水資源供水效益與風險之影響分析

Abstract

近年來由於全球性的氣候變遷，導致極端水文事件較以往大幅增加，間接造成水庫供水可靠度降低。然而以往水庫供水風險評估，多以長期操作之觀點，分析系統之長期平均效益，惟此並無法真正反映出極端水文下如乾旱或洪水而引起的高濁度時的缺水問題。 緣此，本計畫目的擬以石門水庫為對象，完成在極端水文條件下如枯水期或是洪水所引起的高濁度等，對水庫供水風險的影響分析，以做為石門水庫永續經營之參考。

Owing to the global climate change, the extreme shortage events occur more frequently then ever and the water shortage risk is increasing. The traditional analysis of water supply risk focused on evaluating the long-term system performance. However, the study may not resolve the general concern on water supply. People concern more on the water shortage in extreme hydrological condition such as dry or flood season then just an average system performance. Hence, this study analyzes the water shortage risk in extreme hydrological condition under global climate change, such as water deficit in dry season and shortage caused by high turbidity in reservoir. The study began at downscaling the Global Climate Chang Model (GCM) data to local (Shihmen Reservoir watershed) basin rainfall. Multiple rainfall data were then synthesized. GWLF model was used to transfer the rainfall into basin runoff. The runoff is the input to the water allocation model developed by using system dynamics method. Base on the synthesized data and water allocation model, this study applied Monte Carlo simulation to analyze water shortage risk analysis during dry season. Moreover, because the reservoir storage can always fufill demands during flood, the water supply simulation can be simplified by considering only the reservoir turbidity and water treatment plant capacity during flood. Since some of the turbidity observations data were missed, an Artificial Neural Network (ANN) was trained to interpolate the missing data in six typhoons. The amount of water supply in high turbidity was simulated using system dynamic and its risk was determined by the occurring probability of the associated typhoon events. The analysis of system performance in dry season and high turbidity condition can be a valuable reference for the sustainable management of Shimmen Reservoir.