圖書典藏及影音數位平台

為能審慎評估全球氣候變遷可能造成之衝擊及相關調適策略，詳予考慮我國國情、體制、資源、與研發及實務工作之人力及本署應有作為，本署業已於98年度執行完成「氣候變遷對水環境之衝擊與調適研究計畫」第1階段管理計畫，規劃於四年內(99~102年)推動「氣候變遷對水環境之衝擊與調適研究計畫」科技研究發展專業計畫(以下稱主計畫)，以為本署因應全球氣候變遷可能對水資源、旱災、防洪及海岸防護等掌理事項造成之衝擊及其調適策略奠定基礎。 本分項計畫為主計畫中之氣候變遷水文因子情境設定研究計畫之ㄧ，其目的係為評估氣候變遷對台灣地區降雨、颱風、河川流量等水文環境因子之衝擊影響與風險，針對這些水文環境因子進行量體、時間與空間上分布的變異分析，以推估未來設定目標年之氣候變遷情境，並探討其不確定性之風險問題，作為研擬因應氣候變遷調適策略及行動計畫之參考。

Aiming to assess the impact of climate change on water resources and formulate adaptation strategies, Water Resources Agency (WRA) initiated a four-year (2010 - 2013) Climate Change Impact and Adaptation Program (CCIAP). Due to the nature of water resources planning and design for which WRA bears the administrative responsibility, it is imperative for CCIAP to consider the impact of climate change at local and event scales. Thus, among a group of CCIAP projects, this project aims to assess the impact of climate change on event rainfall and streamflow properties in Taiwan, and to evaluate the temporal and spatial variations of these impacts and their risks, in a period of two years. Firstly, relevant literature pertaining to the objectives of this study is collected. Climatological and hydrological data from Dan-shui River, Wu River, Chou-shui River, Tseng-Wen River, and Kao-Ping River watersheds have also been collected for assessing climate change impacts. The storm properties (duration, total depth, and inter-event-time) of four different storm types (mei-yu, convective, typhoon, and frontal rainfalls) are analyzed. Secondly, based on the GCM outputs under the A1B, A2, and B1 scenario provided by National Science and Technology Center for Disaster Reduction (NCDR), the future daily rainfall sequences are generated. To derive the storm properties from the daily rainfall sequences, an artificial neural network (ANN) model has been developed. Thirdly, a stochastic storm rainfall simulation model (SSRSM) has also been developed to generate large set of annual sequences of hourly rainfall for the projection period of 2020 - 2039 using the storm properties derived from the ANN model. Outputs of the SSRSM have also been tested and proven to be very useful for assessing the impact of climate change on rainfall and streamflow properties, under given climate change scenarios. Fourthly, a streamflow simulation model has been developed to generate large set of annual sequences of hourly streamflow for the projection period of 2020 - 2039 using the hourly rainfall data resulting from the SSRSM model. Then, the frequency analysis of these hourly rainfall and streamflow data are performed. The variation of the rainfall and streamflow properties due to climate change is also discussed. The impact of climate change on event rainfall and streamflow properties in Taiwan is evaluated. Finally, based on the results, the future quantity of event rainfall and streamflow is designed.