博碩士論文 106626004 完整後設資料紀錄

DC 欄位 語言
DC.contributor水文與海洋科學研究所zh_TW
DC.creator黃振洋zh_TW
DC.creatorZHEN-YANG HUANGen_US
dc.date.accessioned2021-1-26T07:39:07Z
dc.date.available2021-1-26T07:39:07Z
dc.date.issued2021
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=106626004
dc.contributor.department水文與海洋科學研究所zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract台灣地區年降雨量雖豐沛,但時空分配不均,加上地狹人稠與地勢陡峭,使得河川短而急,水庫庫容不足以有效蓄積豐水期降水,然而由於水庫在臺灣地區的水資源調配使用卻又扮演相當重要的角色,因此當旱象發生時,水庫的有效蓄水往往無法支應社會需求,例如2020年5月17日時石門水庫的有效蓄水量只有33%,即使到10月底時也只有50%,而氣候變遷對水庫的可能影響更將直接衝擊未來可用水資源的多寡,本研究目的在探討氣候變遷對於石門水庫集水區的影響,採用台灣氣候變遷整合服務平台(Taiwan Climate Change Projection Information and Adaptation Knowledge Platform ,簡稱TCCIP)提供之IPCC AR5網格化水文氣象資料,包含34種GCMs搭配4種代表濃度路徑(Representative Concentration Pathways,簡稱RCPs),以氣候變遷下水資源風險整合評估模式(Taiwan Water Resource Assessment Program to Climate Change,簡稱TaiWAP)評估石門水庫集水區未來之水文變遷,並分析在不同時期下年尺度和月尺度之降雨、氣溫和流量的可能變化。 研究結果顯示,石門水庫集水區從2021年至2100年,所有GCMs平均值在年尺度下降雨、氣溫與流量都呈現增加之趨勢,月尺度下的降雨與流量的增加集中在5至10月豐水期,使得未來豐水期期間之強降雨發生機率將會大幅增加,在有限庫容下,對未來水資源應用及調適上帶來衝擊與挑戰。考量氣候變遷推估資料的不確定性與更完整呈現推估資訊,針對4個不同未來時期(近未來、中未來、遠未來與世紀末)與各RCPs情境下,以General Circulation Models (GCMs)的增減模式個數計算降雨、氣溫與流量之增減機率,並將最大與最小極端推估值之GCM模式推估資料整理列表,可提供後續研究時GCM模式選取參考依據,更全面性的完整探討石門水庫集水區未來之降雨、氣溫與流量變化。zh_TW
dc.description.abstractAlthough the annual rainfall in Taiwan is abundant, its spatial and temporal distributions are quite uneven. Owing to steep terrains, rivers in Taiwan are often short and rapid causing challenges in water resources managements due to limited reservoir capacities. Whenever droughts occurred, the effective water storage of our reservoirs are often unable to meet societal needs. For example, the effective water storage of the Shihmen Reservoir was only 33% on May 17, 2020, and only 50% by the end of October. Furthermore, impacts of climate change will affect functions of reservoirs to support water resources managments. The purpose of this study is to investigate impacts of climate change of the Shihmen Reservoir. Projections of the IPCC AR5 gridded hydrometeorological data from the Taiwan Climate Change Projection Information and Adaptation Knowledge Platform (TCCIP), including a total of 34 General Circulation Models (GCMs) with 4 Representative Concentration Pathways (RCPs), were adopted to perform hydrological simulations of the Shihmen Reservoir with the Taiwan Water Resource Assessment Program to Climate Change (TaiWAP) model. Changes of rainfall, temperature, and inflow were analyzed with annual and monthly scales. Projections of annual rainfall, temperature, and inflows of the Shihmen Reservoir Watershed show an increase trend from 2021 to 2100 based on the average of all GCMs adopted in this study. On the monthly scale, significant increases of rainfall and inflow were observed for the wet season from May to October. Higher probabilities of heavy rainfall during the wet season should be noted. With limited reservoir capacity, challenges of adopting suitable adaption measures for sustainable water resources managements will be more profound to the Shihmen Reservoir watershed. Considering the uncertainty of climate projections, probabilities of increase or decrease in rainfall, temperature, and inflow were calculated based on numbers of GCMs having increase or decrease projections at 4 different future time periods (namely near future, mid future, far future and the end of the century). Meanwhile, the maximum and minimum projected changes in rainfall and temperature were given with the corresponding GCMs in tables for cases of outliers to provide comprehensive information for future studies.en_US
DC.subject氣候變遷zh_TW
DC.subject石門水庫zh_TW
DC.subject模式應用zh_TW
DC.subjectIPCC AR5zh_TW
DC.subjectShihmen Reservoiren_US
DC.subjectClimate Changeen_US
DC.subjectImpact Assessmenten_US
DC.subjectIPCC AR5en_US
DC.title氣候變遷下石門水庫集水區衝擊評估: AR5多模式推估資料之應用zh_TW
dc.language.isozh-TWzh-TW
DC.titleClimate Change Impact Assessment on the Shihmen Reservoir Watershed: Application of Gridded Multi-model AR5 Projectionsen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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