tai ccat複審 總計畫3
TRANSCRIPT
總計畫 評估組
環境組 治理組
TaiCCAT主持人:劉振榮 副校長
總計畫 評估組
環境組 治理組
氣候變遷調適科技整合研究計畫Taiwan integrated research program on Climate Change Adaptation Technology
簡報內容 計畫背景 總體目標 研究挑戰 推動架構 推動歷程 理論基礎 跨組連結( 總計畫與三組報告 ) 主要工作 預期成果
計畫背景 由於氣候變遷衝擊顯著,但卻具有高度的不確定性,臺灣社會應儘早建立全面的調適作為予以因應,以維護人民生命財產、環境生態與國家永續發展,且需考量高不確定性以避免做出錯誤決策。
承續「永續台灣的遠景與策略」及「氣候變遷衝擊調適及因應策略」計畫成果,並考慮國內學界與施政單位有關氣候變遷相關研究之整合必要,推動「氣候變遷調適科技整合研究計畫」。
本計畫為行政院國家永續發展委員會「科技與評估組」 (國科會 ) 之重要計畫,藉由調適科技之推動,支援政府決策,並促進國際合作,以減少生態環境與經濟社會系統脆弱度並提升回復能力。
總體目標 支援各部會落實科學研究 氣候變遷調適科技學術缺口鑑別與研究發展 民眾認知與合作機制之重要性 氣候變遷資訊高不確定性與知識不完整性,需要系統整合,並強化環境監測與評估能力,已發展具有強健與富有彈性之調適能力
風險評估、風險分攤、風險治理 現況與未來風險之掌握 產官學民、跨部會風險共同承擔 財務、土地規劃、科技、產業推動
掌握風險資訊(監測、評估)、合理措施(調適措施)、智慧決策(風險治理、土地規劃)、尋找機會(科學與產業發展)
建構各部會因應氣候變遷衝擊所需科技與現有科學知識之橋梁 科學知識於科技發展應用之可行性分析 科技發展所需前瞻科學研究規劃
建構整合研究架構 鑑別跨部會氣候變遷關鍵議題與技術需求 發展不同空間尺度跨領域議題之研究架構 資訊需求與規格
研究挑戰 跨領域性:氣候事件是個綜合環境、文化與政策的複雜現象
不確定性:氣候變遷仍具高度科學不確定性,並須設法喚醒民眾因應意識
高急迫性:氣候事件已在台灣發生,必須盡快檢視並改善我們的環境
因地制宜:氣候調適沒有標準規範,因人與所處環境而異,必須因地制宜
風險分散:由於上述特性,氣候變遷會顯著衝擊,但又具高不確定性,必須將風險分散,並因地制宜,且能彈性調配與系統整合。
農業生產及生物多樣性 能源供給及產業
維生基礎建設 土地使用
水資源健康海岸
災害
計畫定位行政院永續發展委員會
科技與評估組 ( 國科會 )
氣候變遷研究聯盟(CCliCS)
台灣氣候變遷推估與資訊平台(TCCIP)
氣候變遷調適科技整合研究計畫 (TaiCCAT)
環境監測分析 ( 環境組 )
脆弱度評估 ( 評估組 )
調適治理 ( 治理組 )
整合推動 ( 總計畫 )
經建會 (2012.6)國家氣候變遷調適政策綱領
農業生產及生物多樣性 能源供給及產業
維生基礎建設 土地使用
水資源健康海岸
災害
計畫定位行政院永續發展委員會 經建會
國家氣候變遷調適政策綱領 (2012.6)
科技與評估
( 下游 )氣候變遷調適科技整合研究計畫
(TaiCCAT)
(Patt, 2012)
推動架構國科會
環境組 評估組
總計畫
臺灣大學童慶斌教授海洋大學李光敦教授成功大學蘇慧貞教授臺灣大學盧虎生教授中興大學林幸助教授中央大學李明旭教授
海洋大學李明安院長中央大學李錫堤教授中央大學陳良健教授中央大學林唐煌教授臺灣大學李培芬教授成功大學許泰文教授
中研院 張靜貞教授台北大學詹士樑教授清華大學范建得教授
主持人:中央大學劉振榮副校長 執行秘書:中央大學李河清教授
治理組
Climate
減災措施 減災能力建構
過去 未來
脆弱度評估
調適治理
先期調適( 過去經驗 )
計劃調適( 未來規劃 )
自發調適( 近程調適 )
現在
環境系統分析
氣候調適能力建構
Weather
脆弱度評估
推動歷程
整合運作
社會大眾
政府學術
環境系統分析
調適治理
第一階段研究架構
第二階段研究發展
第三階段整體推動
核心分組 第一階段:規劃 第二階段:先期計畫
總計畫
1. 完成國內外氣候變遷調適科技研究現況與研究缺口分析
2. 研究架構規劃,確立總計畫辦公室與三個核心分組。
3. 形成研究團隊與階段推動策略
1. 研究規劃與整合之強化2. 調適科技國際交流與合作管道建立3. 風險治理與空間規劃分析4. 知識平台規劃5. 科學報告規劃
環境監測組
1. 熱島效應2. 崩坍預測模式 (Shihmen Reservoir)
3. 臺灣海峽海溫上升分析4. mullet fishery 糧食安全分析5. 海空交互作用-澎湖冷水入侵災害6. Land-sea interaction for sand
reduce
脆弱度評估
1. 跨領域研究問題分析2. 各領域標準評估流程3. 資訊流分析與問題釐清4. 跨領域脆弱度評估系統動力模式5. 脆弱度與回復力指標系統
調適治理
議題矩陣五:調適治理觀點下的跨組連結
Climate
減災措施 減災能力建構
過去 未來
脆弱度評估
調適治理
先期調適( 過去經驗 )
計劃調適( 未來規劃 )
自發調適( 近程調適 )
現在
環境系統分析
氣候調適能力建構
Weather
議題矩陣三:脆弱度評估觀點下的跨組連結
Climate
減災措施 減災能力建構
過去 未來
脆弱度評估
調適治理
先期調適( 過去經驗 )
計劃調適( 未來規劃 )
自發調適( 近程調適 )
現在
環境系統分析
氣候調適能力建構
Weather
議題矩陣四:環境系統分析觀點下的跨組連結
Climate
減災措施 減災能力建構
過去 未來
脆弱度評估
調適治理
先期調適( 過去經驗 )
計劃調適( 未來規劃 )
自發調適( 近程調適 )
現在
環境系統分析
氣候調適能力建構
Weather
議題矩陣一:部會觀點下的跨組連結
議題矩陣二: IPCC AR5 觀點下的跨組連結
1818計畫網絡分析
主要工作 總計畫 環境組 評估組 治理組
核心分組 各分組主要目標
總計畫1.提高民眾氣候變遷脆弱度調適科技認知2.建構產、官、學界溝通知識平台3.促進氣候變遷調適科技國際合作
環境組1.提供監測資料加值分析之資訊以掌握生態環境狀態與變化趨勢2.發展以長期監測資料為依據之應變性調適科技3.提出強化監測系統之監測能力建構
評估組1.發展跨領域脆弱度評估之方法與工具以瞭解未來之挑戰2.發展以中長期評估為依據之規劃性調適科技3.提供脆弱度與回復力指標系統與評量工具
治理組1.發展風險治理工具2.發展土地規劃方法3.科學技術輸出與合作架構與流程
核心分組 各分組主要工作項目
總計畫1. 撰寫科學報告2.建構產、官、學界知識平台與發展風險溝通方法與機制3.推動氣候變遷調適科技國際合作
環境監測組
1.提供監測資料加值分析之資訊以掌握生態環境狀態與變化趨勢2.發展以長期監測資料為依據之應變性調適科技3.提出強化監測系統之監測能力建構4. 示範計劃推動
脆弱度評估
1.發展跨領域脆弱度評估之方法與工具以瞭解未來之挑戰2.發展以中長期評估為依據之規劃性調適科技3.提供脆弱度與回復力指標系統與評量工具4. 示範計劃推動
調適治理
1.發展風險治理工具2.發展土地規劃方法3.科學技術輸出與合作架構與流程4.社會、人文、與法制議題規劃
環境監測組 脆弱度評估組 調適治理
鑑別問題 跨領域問題
DIKW IKW
工具發展
1. 跨領域評估工具2. 各領域評估工具指標與評量系統
3. 資訊規格與轉換
調適科技
知識平臺
科學報告
總計畫
簡報:劉振榮 副校長
總計畫 環境組 評估組 治理組
屬性 D1
D2
D3
D4
D5
D6
S1
S2 S3 S4 S5 S6R1
R2 R3
跨組性
網絡性
整合性
創新性
海洋監測
資料加值
大氣監測
陸地監測
地質監測
海岸監測
生態監測
脆弱評估
能力建構
環境災害
公共衛生
糧食安全
生態系統
水資系統
風險管理
科技規劃
國土規劃
調適科技推動
跨組運作
統籌規劃
示範計畫
國際網絡
整合產出
科學報告
知識平台
評量系統
社會大眾
政府學術
規劃
執行
修正
「台灣氣候變遷推估與資訊平台建置計畫」(TCCIP)
「氣候變遷研究聯盟」(CCliCS)
子項工作
總計畫相互支援
相互支援
彙編氣候變遷衝擊與調適科學報告
發展土地利用規劃之氣候調適措施
氣候衝擊與永續環境科技規劃報告( 總體研究統籌與規劃 )
IPCC AR5 WGII相關章節
國家氣候變遷調適政策綱領 ( 草案 ) 與
部會行動計畫對應支援
建構氣候變遷衝擊與調適知識平台
建立氣候調適研究國際網絡
TaiCCAT 執秘
子計畫 D1 ( 召集 ), D2, D3, D4, D5, D6
環境組
子計畫 S1 ( 召集 ), S2, S3, S4, S5, S6
評估組
子計畫 R1 ( 召集 ), R2, R3
治理組
建立氣候變遷衝擊與調適評量系統
TaiCCAT 副執秘
類 別 姓名 服務機構 /系所 職稱在本研究計畫內擔任之
具體工作性質、項目及範圍*每週平均投入
工作時數比率 (%)
總計畫主持人
劉振榮國立中央大學
太空及遙測研究中心
教授副校長
氣候衝擊與永續環境科技規劃報告( 總體研究統籌規劃 )
( 子項工作 1)
20%
共同主持人
童慶斌(評估組召集 )
國立台灣大學生物環境系統工
程學系
教授主任
氣候變遷衝擊與調適科學報告彙編( 子項工作 2)
氣候變遷衝擊與調適知識平台建構
( 子項工作 3)
20%
共同主持人
李明安(環境組召集 )
國立海洋大學海洋科學與資源
學院
教授院長
20%
共同主持人
張靜貞(治理組召集 )
國立台灣大學中央研究院
教授研究員
20%
共同主持人
王國英國立中央大學環境研究中心
教授主任
20%
共同主持人
詹士樑國立台北大學不動產與城鄉環
境學系
教授主任
示範計畫土地使用規劃之氣候調適措施發展
( 子項工作 4)
20%
共同主持人
李河清國立中央大學通識教育中心
教授氣候調適研究國際網絡建立
( 子項工作 5)20%
博士後研究
江益璋國立中央大學環境研究中心
博士後研究員
支援子項工作 1, 4, 5;支援治理組協同評估組建立
氣候變遷衝擊與調適評量系統100%
博士後研究
李家齊國立中央大學環境研究中心
博士後研究員
支援子項工作 1, 2, 3;支援評估組協同治理組建立
氣候變遷衝擊與調適評量系統100%
運作機制 宗旨:跨組協調、進度掌握、成果發表、相關部會與研究單位
協調與聯繫、整合工具與資訊平台建立 辦公室 (推動小組 )
主持人:劉振榮副校長 執行秘書:李和清教授 副執行秘書:童慶斌教授 環境組代表:李明安院長、林唐煌教授 評估組代表:盧虎生教授、蘇慧貞教授 調適組代表:張靜貞教授、詹士樑教授 博士後研究人員、研究助理、行政助理
會議 參與各組會議與進度訪視:每月 推動小組會議:每季召開 諮詢委員會:半年召開
研究產出說明
鑑別問題現況災害問題、跨領域問題、空間分散風險問題、民眾與政府共同承擔風險問題、產業與科技發展機會
資料分析 監測資料、評估模式所需資料、氣候推估資料
工具發展 資料資訊轉換工具、評估工具、溝通工具、決策工具
調適科技 軟性科技與硬性科技
知識平台問題說明、 DIKW、標準流程、評估工具、調適知識與科技
科學報告 現況分析、未來挑戰評估、調適措施研擬、未來機會探討
國際網絡 方法文件標準化、尋求合作夥伴、發展推廣策略
總計畫 環境組 評估組 治理組D1
D2
D3
D4
D5
D6
S1
S2 S3 S4 S5 S6R1
R2 R3
示範計畫
國際網絡
統籌規劃
科學報告
評量系統
知識平台
海洋監測
資料加值
大氣監測
陸地監測
地質監測
海岸監測
生態監測
脆弱評估
能力建構
環境災害
公共衛生
糧食安全
生態系統
水資系統
風險管理
科技規劃
國土規劃
S
D
R
ik資訊詮釋知識發展
di資料加值資訊提供
kw知識應用智慧發展
[脆弱度 ]
[ 暴露度 ]
[調適力 ]
提出需求
提出需求
統籌規劃
Ddi-Sik-Rkw
都會 鄉村 山地 海岸 流域 離島
總計畫 環境組 評估組 治理組D1
D2
D3
D4
D5
D6
S1
S2 S3 S4 S5 S6R1
R2 R3
示範計畫
國際網絡
統籌規劃
科學報告
評量系統
知識平台
海洋監測
資料加值
大氣監測
陸地監測
地質監測
海岸監測
生態監測
脆弱評估
能力建構
環境災害
公共衛生
糧食安全
生態系統
水資系統
風險管理
科技規劃
國土規劃
示範計畫
Ddi-Sik-Rkw
ik資訊詮釋知識發展
kw知識應用智慧發展
S R[脆弱度 ]
[調適力 ]
di資料加值資訊提供
D[ 暴露度 ]
不要堤防的居民?
訪談:總計畫 + 評估組 + 水規所 (2011.10.28) 聚落:東石鄉網寮漁村 ( 海岸地區 ); 環境:地層下陷區、外水 ( 海水 )高於內水;
1986(淹 30天 )、 1990(淹 39天 )、 1992(淹 13天 ) 情境:不常淹水、堤防「圍村」且不便漁業 調適:傢俱墊高 鹽田滯洪 跳上漁筏 觀點:當科學知識遇到地方知識
海岸
都會
鄉 (漁 )村
都會 鄉村 山地 海岸 流域 離島
國際網絡資料加值 監測科技 資訊解讀 評估科技 知識應用 調適科技
氣 候 變 遷 調 適 科 技 推 動
3636
2011
2012
3737
芬蘭:論文發表the Second Nordic International Conference on Climate Change
Adaptation, Helsinki, Finland, 29-31; http://www.nordicadaptation2012.net/
德國:知識平台Climate Service Center, Hamburg; http://www.climate-service-center.de/
德國:科技法律Center for Environmental Research - UFZ; http://www.ufz.de/index.php?
en=11382
荷蘭:示範計畫Delft University of Technology, Department of Urbanism;
http://www.bk.tudelft.nl/en/about-faculty/departments/urbanism/
日本:論文發表International Conference on Science and Technology for Sustainability;
http://www.scj.go.jp/ja/int/kaisai/jizoku2011/program.html
英國:論文發表Planet Under Pressure 2012; http://www.planetunderpressure2012.net/
美國:論文發表ISA ANNUAL CONVENTION 2012; http://www.isanet.org/blog/2011/04/cfp-
isa-annual-convention-2012.html
荷蘭:洪水治理UNESCO-IHE Institute for Water Education; http://www.unesco-ihe.org/
台灣:國際會議International Symposium on Climate Change Adaptation Technology, 15
September 2012, Taiwan; http://taiccat2012.blogspot.tw/
菲律賓:糧食安全International Rice Research; http://www.irri.org/
歐盟:評量系統CLIMSAVE - climate change integrated assessment methodology for
cross-sectoral adaptation and vulnerability in Europe; http://www.climsave.eu
美國:論文發表24th Annual Conference International Society for Environmental
Epidemiology; http://saeu.sc.edu/reg/isee2012/
Regional climate models
Agriculture and forestry
Energy economics
Water management
Coastal protection
Urban planning and building
Education and communication
Tourism
Traffic
39
2008 to 2014
7 joint regional projects
about 80 million €
4141
德國 UFZ :調適法規 荷蘭 Delft :空間規劃德國 CSC :氣候資訊
芬蘭 會議:成果發表荷蘭 Delft :研究交流德國 KomPass :知識平台
芬蘭 會議: IPCC-TaiCCAT交流德國 CSC :研究交流荷蘭 Delft :低地考察
IPCCRichard Klein
TaiCCAT江益璋
IPCC SREX Lead AuthorProf. Richard Klein 意見 (2012.9.28): Judging from the information
provided (TaiCCAT poster), this is a large and ambitious programme.
It's good to see the emphasis on governance, and the integration with disaster risk reduction.
I would be interested in reading more about the programme.
芬蘭 會議:成果發表
芬蘭 會議: IPCC-TaiCCAT交流
IPCCRichard Klein
TaiCCATYi-Chang Chiang
評估組發表 環境組發表芬蘭專題
治理組發表 大會貴賓 德國專題
綜合討論總計畫發表荷蘭專題
氣象局程主任意見 (2012.9.16) ( 張靜貞老師提供 ): CWB is trying to find partners in various
application areas to promote end-to-end services. I believe TaiCCAT project would be a very good partner that CWB could work with.
綜合討論
I do hope that TaiCCAT would so like to cooperate with government agencies and/or act as a bridge to link government agencies (supplier and consumer) together for better decision making.
總計畫 環境組 評估組 治理組
D1 D2 D3 D4 D5 D6 S1 S2 S3 S4 S5 S6 R
1 R2 R3
海洋監測
資料加值
大氣監測
陸地監測
地質監測
海岸監測
生態監測
脆弱評估
能力建構
環境災害
公共衛生
糧食安全
生態系統
水資系統
風險管理
科技規劃
國土規劃
CASE TAIWANTechnical report
科學報告
知識平台
人類環境氣候
暴露度 脆弱度 調適力
Data
information
knowledge
wisdom
脆弱度評估環境系統分析 調適治理
Driver Response
State
D di S ik R kw
資料加值 監測科技 資訊解讀 評估科技 知識應用 調適發展
氣 候 變 遷 調 適 科 技 推 動
評量系統學術 大眾 政府
鑑別問題 v v v
DIKW DIKW IK KW
工具發展 v v
調適科技 v v v
知識平臺 v v v
科學報告 v v v
核心分組 各分組主要工作項目 第一年 第二年 第三年
總計畫1. 撰寫科學報告2.建構產、官、學界知識平台與發展風險溝通方法與機制3.推動氣候變遷調適科技國際合作
環境組
1.提供監測資料加值分析之資訊以掌握生態環境狀態與變化趨勢2.發展以長期監測資料為依據之應變性調適科技3.提出強化監測系統之監測能力建構4. 示範計劃推動
評估組
1.發展跨領域脆弱度評估之方法與工具以瞭解未來之挑戰2.發展以中長期評估為依據之規劃性調適科技3.提供脆弱度與回復力指標系統與評量工具4. 示範計劃推動
治理組
1.發展風險治理工具2.發展土地規劃方法3.科學技術輸出與合作架構與流程4.社會、人文、與法制議題規劃
核心分組 各分組預期成果
總計畫
1.完成科學報告2.完成產、官、學界知識平台3.提出風險溝通方法與機制4.建立實質氣候變遷調適科技國際合作計畫
環境組
1.提供監測資料加值分析之資訊以掌握生態環境狀態與變化趨勢2.發展以長期監測資料為依據之應變性調適科技3.提出強化監測系統之監測能力建構4. 示範計劃推動
評估組
1.發展跨領域脆弱度評估之方法與工具以瞭解未來之挑戰2.發展以中長期評估為依據之規劃性調適科技3.提供脆弱度與回復力指標系統與評量工具4. 示範計劃推動
治理組
1.發展氣候變遷風險治理工具2.發展氣候變遷土地規劃方法3.科學技術輸出與合作架構與流程4.社會、人文、與法制議題規劃
環境組
簡報:李明安 教授
環境組 目標:掌握氣候與生態環境現況變化趨勢與研究發展以監測為依據之近程因應措施,強化監測系統
組成: D1: D2: D3: D4: D5: D6:
這一年來的重要成果: Urban heat Island Landslide prediction model (Shihmen
Reservoir) SST rise in Taiwan Strait Environment & food security for mullet
fishery Air-sea interaction for peng-hu cold water
intrusion Land-sea interaction for sand reduce
Urban Heat Island over Greater Taipei Region (GTR)
ISA1990
Tb1990
UHI1990
ISA1996
ISA2005
Tb1996
Tb2005
UHI1996
UHI2005
(Landsat data used from 1990 to 2009)
+ Brightness temperature of test areas in different season(1999-2003)
U2
U1
U3
R1
R2S3
R3
S1
S2
area1
area2
area3
• U1: Urban1• U2: Urban2• U3: Urban3
• S1: Suburban1• S2: Suburban2• S3: Suburban3
• R1: Rural1• R2: Rural2• R3: Rural3
(Size: 50x50 pixels)
• Forest• Taipei
metropolitan
spring summer winter
Taiwan 20.09 25.06 18.95
Urban 25.12 29.82 22.76
Plain 24.87 26.87 21.13
Tableland 22.4 23.87 20.71
Mountain 14.52 15.99 11.31
12
16
20
24
28
Brightness temperature (Tb) in different season
Bri
ghtn
ess
Tem
per
atu
re (
C
)
582012/2/23
Investigation of UHI and regional precipitation
2000
2100
2200
2300
2400
2500
2600
Year
prec
ipit
ati
on
(mm
)Urban Precipitation (1987~2010)
3
4
5
1961 1969 1977 1985 1993 2001 2009
Year
UH
II(℃
)
Taipei Heat Island (1972~2009)
1000
1500
2000
2500
3000
1940~1950 1950~1960 1960~1970 1970~1980 1980~1990 1990~2000 2000~2010
Pre
cip
itio
n(m
m)
4000
4500
5000
5500
Pre
cip
ition
(mm
)
台北站 竹子湖站
Urban and Rural Precipitation
50 10 15 20 25 30 35 40 45 5050 10 15 20 25 30 35 40 45 50
120 E 122 E
MODIS/Terra 2000/07/14 03:10 UTC
25 N
23 N
℃ 50 10 15 20 25 30 35 40 45 5050 10 15 20 25 30 35 40 45 50
120 E
25 N
122 E
23 N
℃
MODIS/Terra 2008/07/24 0230 UTC
2000
38.7
36.3
31.1
36.136.9
28
30
32
34
36
38
40
LS
T(
℃)
33.3
35.5
31.2
32.6
35.4
28
30
32
34
36
38
40
2000 2002 2004 2006 2008Year
LS
T(
℃)
Taipei City
Kaohsiung City
2008
~1990
訓練樣區 NDVI 時序資料
Urban development and heat island over Greater Taipei Region (1990-2009)
60
Land Surface MonitoringWork Scopes
1. Statistical models for landslide and debris flow prediction: Following Lee et al. (2008),we develop new models for landslide and debris flow prediction, and apply to drainage basin of the Shihmen
Reservoir and the Tsengwen River basin. Prediction under extreme rainfall condition will be discussed also.
2. Soil depth estimation: We develop empirical formula for estimation of soil depth at hill slopes by using local data. This formula will be used in estimation of sediment budget and calculation of sediment transport.
3. Simplified method for estimation of sediment budget: Using results from landslide prediction and soil depth estimation, we calculate sediment
budget in each drainage basin. This result can be used to compare with the result from our drainage basin sediment transport system.
4. Geostatistical interpolation of rainfall parameters: Topographic data are joined with rainfall data and a regression Kriging method is used
to perform interpolation for different rainfall parameters. These will be used in landslide and debris flow prediction models and in the drainage
basin sediment transport system.5. Developing a drainage basin sediment transport system: Surface
erosion and channel transport mechanisms will be added in to a drainage basin hydrological model to develop a sediment trasport system.
61
Topographic data, hydrological data, geological data, landslide and debris flow data, and landuse data
DEMGeologic
MapActive Faults
Landslides
Debris Flows
Land Surface MonitoringData Collections
62
Topographic data, hydrological data, geological data, and landuse data, etc. are processed and further used in establishing a
statistical prediction model.
Rainfall Intensity
Slope Slope Roughness
Profile Curvature
NDVI Lithology
Relative Height
Total Slope Height
Wetness Index
Distance to Fault
Land Surface MonitoringData Analysis for landslide prediction
model
63
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1
0.64030.007587( )1slP
AUC=0.856
LS sus.index,λ
LS prob., P
sl
Landslide probability curve for Typhoon Aere
Success rate for model AereLandslide probability map under
Aere rainfall
Portion of area
Success
rate
Landslide probability map for Typhoon Aeret and for 100-year return period rainfall at drainage basin of the Shihmen Reservoir
( 石門水庫 ).
Landslide probability map under 100-year return period rainfall
Land Surface MonitoringLandslide Prediction model
Figure Distribution of oceanographic station data around Taiwan (>150,000 sts).
Mapped are all available data from the World Ocean Database‐2009, updated 2011‐04‐21. Shown are only those stations that have both temperature (T) and salinity (S).
Created by Daphne Johnson, National Oceanographic Data Center, NOAA.
-1
-0.5
0
0.5
1
1.5
1981 1984 1987 1990 1993 1996 1999 2002 2005 2008
年別
SST
A (℃
)
SSTA
-1.5
-1
-0.5
0
0.5
1
1.5
2
1957
1960
1963
1966
1969
1972
1975
1978
1981
1984
1987
1990
1993
1996
1999
2002
2005
2008
年別
SS
TA
(℃)
SSTA
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
1981 1984 1987 1990 1993 1996 1999 2002 2005 2008
年別
SST
A (
℃)
SSTA
SST increase 1℃
SST increase1.2℃SST increase 1.1℃
SST increase +1.15±0.19 /100 yr ℃
(Source:本研究團隊 )
(Source: nagasaki uni.)
Multi-decadal variability of oceanic climate in the Taiwan Strait was studied using sea surface temperature (SST), which is the most conveniently measured and frequently observed variable related to maritime
climate. We used the 1 degree x 1 degree monthly climatology of SST available from the U.K. Met Office Hadley Centre. Between 1957 and 2011, three distinct regimes were identified. The first regime of fairly
stable or slightly cooling SST lasted through 1976. The regime shift of 1976-1977 led to a super-fast warming of 2.1°C in 22 years, from 23.2°C in 1976 up to 25.3°C in 1998. Another regime shift occurred in
1998-1999, leading to a 1.0°C cooling from 1998 to 2011. The spatial distribution of climate trends across the Taiwan Strait was studied for the first time, revealing a strong spatial gradient along the Strait. In the north (southern East China Sea), the magnitude and rate of the overall SST warming between 1957 and 2011 was
about three times those in the south (northern South China Sea).
Feeding ground
Spawning ground
Grey mullet Caught around
Taiwan has spawning and
nursery grounds in the coastal
waters of southwestern Taiwan, and
feeding grounds of juveniles and
adults are located in the coastal waters
of mainland China about
between latitude 25 and 30 N
Grey mullet
It migrates into the coastal
waters of west Taiwan during
the winter solstice.
Question: The cause of the fluctuation and decline in catch? Overfishing or Climate
change ?
Year
Ca
tch
(1
03n
um
be
r)0
500
1000
1500
2000
2500
3000
1968 1973 1978 1983 1988 1993 1998 2003 2008
Catch
Mean
Since 1958 the annual catch of grey mullet has fluctuated greatly with a peak of 2.54 million fish in 1980 and a minimum of 0.4
million fish in 1990 and 0.2 million in 2000 to 2004. In recent years, it has rapidly declined to about 45 thousands/year in 2007~2009,
causing a concern to its management agency.
2.54 million
Overfishing (Huang et al., 2005)
×
Cross-wavelet coherence between climatic index (a) annual PDO (b) winter WPO (c) autumn ONI and (d) sea surface
temperature with log10 (grey mullet catches).
1958-1978 6–8 yr
8 yr
1–2 yr
2–3 yr
Annual trends of (a) grey mullet catches (black line) and PDO (grey line) and (b) winter SST (black dotted line) from 1958 to
2009.
The annual PDO, the time series trends of annual
catches and PDO showed a fairly good correspondence
A declining trend of the fluctuation in catches and raised trend in winter SST
after 1980s
The PDO might play a role in affecting the grey mullet migrated but the increased of SST would also an important reason caused the
decreased and low catches of grey mullet after 1980.
The catch percentage of grey mullet caught by the Taiwanese fishing boats and collected from the local fisherman
associations in the west coast of Taiwan (a) 1978–1987 (b) 1988–1997 and (c)
1998–2009.
More than 85% of grey mullet was caught in the south of 23.5°N in 1978–1987 in the eastern Taiwan Strait.
In 1988-1997, the fishing grounds moved to north and more than 30% grey mullet was caught in the latitude of 24.5°N where was the low catch fishing ground in 1978–1987, while the parts of fishing grounds moved to north of 25°N after 1998–2008
The latitudinal variation of the 20 °C isotherm of 1958–1967 (purple line), 1968–1977 (brown
line), 1978–1987 (green line), 1988–1997 (blue line), 1998–2009 (Red line), and the IPCC A2
scenario in SSTs of 2050 and 2075 (grey lines) in the western Taiwan in winter.
There is a consistency of north shifted between the grey mullet fishing grounds and the latitudinal variation of the 20 °C isotherm of western Taiwan in winter, while the 20 °C isotherm moved to north of 25°N of the western Taiwan after 1998.The scenario results shows the 20 °C isotherm of wintertime in the west Taiwan will move to 25.5°N in 2050 and cross the 26°N in 2075. The results suggested the climate change caused the increased of SST and weaken the intrusion of the Coastal Current into the Taiwan Strait. Moreover, the phenomena might decreased the abundance of mullet migrated into western Taiwan and shifted the fishing grounds to north part.
Environment- Food security
Air-Sea interaction for observation on Fisheries and Mariculture impact by Extreme Oceanic Environmental Changes in Taiwan
The fishery resource (included cobia and grouper ) disaster with the economic fishery losses about NT$350
million (US$ 11 million) in February 2008.
It suggested that the continuous strong wind might have driven the cold current more southeasterly to the
southern TS and resulted in the great drop in SST.
Sand area in 2009 is smaller 40 % than that in 2012.
FS2 Image (2m) 2009/09/01
2010/09/26
2011/09/30 2012/06/28
Year 2009 2010 2011 2012Area (Ha) 5.59 5.15 3.43 3.40
THE TAICCAT CONFERENCE 09/15 2012
未來工作之預期產品: Urban heat island (UHI) and land use
index Landslide prediction model in Zengwun
Reservoir Ocean warming variability and micro-
climate SST index Dry/flooding, Coast erosion and
inundation index in Chianan Plain. Ci-Gu wetland/Lagoon habitat biodiversity
環境組整合運作方式: 就不同空間類型進行組內資料整合與變遷指標分析;例如:
五都之 UHI and land use ( 大氣與陸地資料整合 ) 曾文水庫邊坡崩蹋預測模式 (地質與脆弱度 - 河川水文資料與
模式整合 ) 澎湖離島之大氣海洋交互預警模式與漁業糧食安全及調適策略分析
嘉南平原旱澇指標 ( 大氣與海洋及 TCCIP資料整合分析 ) 極端環境或微氣候變遷的加值資料分析;例如:
提供在極端氣候 - 颱風之影響下的流域 ( 含水庫 ) 崩蹋預測模式
提供嘉南平原旱澇指標的週期變動加值分析
Environmental system analysis on micro-climate and value-added indicator surrounding Taiwan in next 3-year study
Coast
Ecology
City development
UHIclimat
eplant
geology
Inundation
erosion
landslide
coast
pollution
Dry/floodwarm
Foodfisherydisast
er
Water resourc
eBio-
diversity
Environmental system
monitor and data bank
(monitor and analysis)
simulate
Regional climate(Air-tem、 Precip、
Key factor)&
Auxiliary data(GIS)
Public health
Eco-system
Food Securit
y
Disaster
Vulnerability
Assessment
Water
resource
Interaction of TaiCCAT environment Group and TCCIP
Adaptation
Governance
TCCIP-regional climate model(NCDR)
Micro-
Climate
Key
Factor
Value-
added
analysis
Atmosphere
Land
Geology
Ocean
Datasets now available
TCCIP_precip_1km.monthly.nc
TCCIP_precip_5km.monthly.nc
TCCIP_tavg_1km.monthly.nc
TCCIP_tavg_5km.monthly.nc
TCCIP_tmax_1km.monthly.nc
TCCIP_tmax_5km.monthly.nc
TCCIP_tmin_1km.monthly.nc
TCCIP_tmin_5km.monthly.nc
TCCIP_SPEI_1km.xxm.nc* (xx=01, 02,… 48)
Datasets now available (1 Jan 1960 – 31 Dec 2009)
TCCIP_precip_1km.daily.ncTCCIP_precip_5km.daily.nc
(November 2011)
SPEI: Standardized precipitation – evapotranspiration index
Grid-data from TCCIP
Time period: 1960 –2009Month: 1km/5km
tem、 precipDay : 1km/5km precip
與過去研究或現在其他單位計畫之差異: CCliCS for model development & Scenario and TCCIP for
down-scaling and historical data bank. EA: Focus on Micro-climate change and value-added data analysis.
回應部會不同面向 ( 如多樣性與海岸帶管理 )所需指標之分析 透過 TCCIP, 總計畫 ,環境組 ,脆弱度及調適治理之整合 ,可針
對極端環境或微氣候變遷所帶來的衝擊 ,提出適切回應;例如: 颱風過後 (環境面向 - 大氣 , 陸地 , 海洋與海岸 ), 對養殖漁業
( 糧食與衛生安全 ) 造成衝擊 ,而後續的補償措施 (調適治理 ) 澎湖冷水入侵 (環境面向 - 大氣海洋 )之微氣候變遷造成沿岸
漁業及養殖漁業 ( 糧食與衛生安全 ) 造成衝擊 , ,而後續亦可有適當的調適措施 (調適治理 )
After typhoon, the oyster aquaculture raft was damaged by heavy flooding.
FS2 Image (2m) of 2012/06/08
2012/06/28
Before typhoon, the oyster aquaculture raft was easily
identified by Formosa image.
FS2 Image (2m) of 2012/06/08
-40
-20
0
20
40
60
80
100
120
Day of wind speed > 6 m/s
Dis
tan
ce
of
20
ºC is
ob
ath
refe
rrin
g t
o P
HI (
km
)
02468101214161820222426283032
Da
y o
f w
ind
sp
ee
d >
6 m
/s
Micro-climate case: Warning system of Fisheries and Mariculture to Extreme Oceanic Environmental Changes in Taiwan
-60
-40
-20
0
20
40
60
80
100
<6 7~12 13~18 >19
Period (day)
Dis
tanc
e of
20
isob
ath
refe
rrin
g to
PH
I (km
)
The fishery resource (included cobia and
grouper ) disaster with the economic fishery losses
about NT$350 million (US$ 11 million) in
February 2008.
In 2008 In 2011
More than 1600 and 1000 tons of cage aquaculture fish perished in 2008 and 2011.
http://blog.roodo.com/upupph/archives/15140175.html
Data Source: Central Weather Burial, Taiwan
Cobia, Black king fish(Rachycentron canadum)
Sea Surface Temperature in PHI, 2011.
Flowchart of the decision-making process for cage aquaculture adaptation.
(Marine policy, accepted in 2012)
評估組
簡報:童慶斌 教授
評估組 目標:評估未來氣候變遷風險,界定不同領域議題間問題,發展跨領域脆弱度評估標準分析流程、評估模式與量化指標系統(永續發展、脆弱度與回復力),並訂定資訊規格與研究發展以評估為依據之中長程調適科技。
組成: S1: S2: S3: S4: S5: S6:
治理組
簡報:張靜貞 教授
治理組 目標:檢討政策並提出修正建議,並提出政策預警與
結合風險管理之決策機制,包括土地利用規劃與科學發展與推廣策略。
組成: R1: R2: R3:
這一年來的重要成果: Integrated Risk Assessment
Literature Review Profile of Taiwan Capacity Building
Design Analytical Framework to Enhance economic efficiency of resource
allocation decisions Promote transparent and accountable choices
between multiple options Facilitate inclusive decision-making processes
involving diverse stakeholders Conduct Case Studies
122
Source: Swiss Re Economic Research & Consulting, 2011
1. 天災之經濟損失與保險理賠之差距逐年擴大中
2. 這些經濟損失可以透過各式天災財務工具來管理
Integrated Risk Assessment: Literature Review
圖 1 2010 年前八大巨災經濟損失
22,000
7,800
400 700 550 3,000
9,475 6,100
8,000
200
3,300 2,000 1,450
3,100
25
0
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
智利 海地 紐西蘭 美國Hail 美國 Tornadoes 歐洲Xynthia 巴基斯坦 中國
地震 颶風 水災
未保險之損失 保險損失單位:百萬美元
Source:Munich Re (2011), Overall picture of natural catastrophes in 2010, Newsletter
123
1. 各國開發程度與投保天災險之差異影響到獲得理賠之比例
2. 天災保險與風險分散機制對民間與政府之好處
Source: Swiss Re Economic Research &
Consulting, 2011
資料來源: Jones and Preston (2010)。
Methodology Based on UN Definitions: Risk = Element at Risk* Natural Hazard* Vulnerability Element at Risk: Whether staple production meets demand Vulnerability: Number of events, Econ loss, Population affected Resilience: Per capita income per year
Ranking Criteria :(1) number of disaster per year; (2) percentage of population affected per year; (3) percentage of economic losses in GDP per year; (4) per capita income per year.
Three rankings from different summations, i.e.,
(1)+(2)+(4), (1)+(3)+(4), (1)+(2)+(3)+(4)
Integrated Risk Assessment: Risk Profile of Taiwan
Country
Number of
Disaster per year
(1)
% of Population Affected
(2)
% of Econ
Losses in GDP (3)
Per Capita Income (4)
(no.) score (%) score (%) score
(US$) score
Australia 4.6 1.95 0.28 1.13 0.25 1.37 52,273 1.00 Brunei 0 1.00 0.00 1.00 0.00 1.00 32,049 2.30 Canada 2 1.41 0.00 1.00 0.01 1.01 45,132 1.14 Chile 2.2 1.45 3.54 2.61 3.34 5.00 11,074 4.14 China 23 5.00 8.76 5.00 0.60 1.88 3,871 4.78 Hong Kong 1 1.21 0.04 1.02 0.00 1.00 31,208 2.37 Indonesia 13.2 3.72 0.41 1.19 0.14 1.20 2,585 4.89 Japan 4.4 1.91 0.10 1.04 0.88 2.29 40,100 1.59 Rep of Korea 1.2 1.25 0.02 1.01 0.00 1.00 20,486 3.31 Malaysia 1.6 1.33 0.15 1.07 0.10 1.15 7,785 4.43 Mexico 6.4 2.32 0.91 1.41 0.20 1.30 9,708 4.26 New Zealand 0.8 1.16 2.93 2.34 2.51 4.67 31,904 2.31 P N Guinea 3.2 1.66 0.84 1.39 0.00 1.00 1,357 5.00 Peru 3.2 1.66 1.74 1.80 0.09 1.13 4,681 4.71 The Philippines
19.4 5.00 8.00 4.65 0.25 1.37 1,962 4.95
Russia 2.6 1.54 0.01 1.01 0.05 1.08 10,599 4.19 Singapore 0 1.00 0.00 1.00 0.00 1.00 40,911 1.51
Taiwan 2.2 1.45 2.02 1.92 0.07 1.11 18,194 3.52
Thailand 4 1.82 11.71 5.00 2.74 5.00 4,529 4.72 USA 16.4 4.38 0.94 1.43 0.16 1.23 46,745 1.00 Viet Nam 6.8 2.40 2.05 1.94 0.74 2.08 1,097 5.00
Natural Disaster Risk in APEC, 2007-2011
Data Sources: EM-DAT DB, FAOSTAT, IMF (World Economic Outlook Database, September 2011)
CountryAverage score of
(1)+(2)+(4)Ranking LEVEL
Average score of (1)+(3)+(4)
Ranking LEVELAverage score of (1)+(2)+(3)+(4)
Ranking LEVEL
(1) (1) (1) (2) (2) (2) (3) (3) (3)Australia 1.36 19 L 4.31 18 L 5.44 18 LBrunei 1.43 18 L 4.30 19 L 5.30 19 LCanada 1.19 20 L 3.56 20 L 4.57 20 LChile 2.74 6 H 10.60 4 H 13.21 4 HChina 4.93 1 H 11.66 1 H 16.66 1 HHong Kong 1.53 16 L 4.58 17 L 5.60 17 LIndonesia 3.27 4 H 9.81 5 H 11.00 6 HJapan 1.51 17 L 5.78 15 L 6.83 15 LRep of Korea
1.86 15 L 5.56 16 L 6.57 16 L
Malaysia 2.28 11 L 6.91 11 M 7.98 13 MMexico 2.67 9 M 7.88 8 M 9.30 8 MNew Zealand
1.94 14 M 8.14 7 H 10.48 7 H
P N Guinea 2.68 8 M 7.66 9 M 9.05 10 MPeru 2.72 7 H 7.50 10 M 9.29 9 MPhilippines 4.87 2 H 11.32 3 H 15.97 3 HRussia 2.24 13 M 6.80 12 M 7.81 14 MSingapore 1.17 21 L 3.51 21 L 4.51 21 LTaiwan 2.30 10 M 6.08 14 M 8.00 12 MThailand 3.85 3 H 11.55 2 H 16.55 2 HUSA 2.27 12 M 6.61 13 M 8.04 11 MViet Nam 3.11 5 H 9.48 6 H 11.42 5 H
Natural Disaster Ranking in APEC, 2007-2011
Governance and Institutional Framework
Information and Knowledge Platform
Education and Training
Integrated Risk Assessment: Capacity Building
Successful Adaptation requires Scientific knowledge of climate change
and vulnerability Systematic monitoring of climate,
ecosystem, and social-economic impacts Long-term planning for infrastructure Public education to encourage collective
actions Enforcement on proper societal
adjustment and practices
Design Analytical Framework: Key Elements
1. 發展風險評估工具與決策模式
2. 進行利害關係人之風險溝通
3. 排定優先順序與策略規劃
Design Analytical Tools
132
1. Stochastic Event Module
3. Vulnerability Module
2. Hazard Module
4. Financial Loss Module
Overall Framework of Flood Risk Engineering Model
Case Study: Flood Risk
Policy Options Land Use Planning Building Code Disaster Relief Insurance Program Financing Calculate premiums under different
assumptions on take-up rate. Government’s bottom-layer coverage are
assumed as premium subsidy.
133
Premiums under 4 scenarios with alternative take-up ratesScenario
Take-Up Rate 25% 50% 100% 25% 50% 100% 25% 50% 100% 10% 50% 100%
Estimated Policy# 825,000 1,650,000 3,300,000 825,000 1,650,000 3,300,000 825,000 1,650,000 3,300,000 37,000 185,000 370,000 AAL (NT$ Mill.) 2,738 5,475 10,950 1,575 3,150 6,300 1,163 2,325 4,650 2,160 4,320 4,320
Pure Premium w/o bottom GOV Cover $3,318 $3,318 $3,318 $1,909 $1,909 $1,909 $1,409 $1,409 $1,409 $58,378 $23,351 $11,676
Estimated Policy# 1,075,000 2,150,000 4,300,000 1,075,000 2,150,000 4,300,000 1,075,000 2,150,000 4,300,000 75,000 375,000 750,000 AAL (NT$ Mill.) 324 648 1,296 324 648 1,296 324 648 1,296 605 1,210 1,210
Additional Premium to Include Livingexpense & Electrical & MechanicalEquipment Loss Cover w/ Limit of
NT$20,000
$301 $301 $301 $301 $301 $301 $301 $301 $301 $8,067 $3,227 $1,613
Estimated Policy# 1,900,000 3,800,000 7,600,000 1,900,000 3,800,000 7,600,000 1,900,000 3,800,000 7,600,000 112,000 560,000 1,120,000 AAL (NT$ Mill.) 59 117 234 59 117 234 59 117 234 12 59 117
Additional Premium to Include ConstructedTotal Loss Cover of NT$120 Mill.
$31 $31 $31 $31 $31 $31 $31 $31 $31 $104 $104 $104
Pure Premium w/o bottom GOV Cover -First-Floor Household
$3,349 $3,349 $3,349 $1,940 $1,940 $1,940 $1,440 $1,440 $1,440 $58,483 $23,456 $11,780
Premium w/ additional cost (15%) $3,940 $3,940 $3,940 $2,282 $2,282 $2,282 $1,694 $1,694 $1,694 $68,803 $27,595 $13,859
Pure Premium w/o bottom GOV Cover -Other Household
$332 $332 $332 $332 $332 $332 $332 $332 $332 $8,171 $3,331 $1,718
Premium w/ additional cost (15%) $391 $391 $391 $391 $391 $391 $391 $391 $391 $9,613 $3,919 $2,021
AAL ratio of Bottom 1 bn Layer 30.26% 16.25% 8.49% 44.31% 25.33% 13.35% 48.84% 29.94% 16.65% 40.01% 22.27% 22.27%
Pure Premium w/ bottom GOV Cover of 1billion - First-Floor Household
$2,336 $2,805 $3,065 $1,080 $1,449 $1,681 $737 $1,009 $1,200 $35,084 $18,232 $9,157
Premium w/ additional cost (15%) $2,748 $3,300 $3,606 $1,271 $1,704 $1,978 $867 $1,187 $1,412 $41,275 $21,450 $10,773
Pure Premium w/ bottom GOV Cover ofNT$1 billion - Other Household
$232 $278 $304 $185 $248 $288 $170 $233 $277 $4,902 $2,589 $1,335
Premium w/ additional cost (15%) $273 $327 $358 $218 $292 $339 $200 $274 $326 $5,767 $3,046 $1,571
AAL ratio of Bottom 1.5 bn Layer 41.85% 23.70% 12.65% 58.19% 35.84% 19.68% 62.04% 40.91% 23.97% 53.08% 31.79% 31.79%Pure Premium w/ bottom GOV Cover of
1.5 billion of First-Floor Household$1,947 $2,555 $2,925 $811 $1,245 $1,558 $547 $851 $1,095 $27,440 $15,999 $8,035
Premium w/ additional cost (15%) $2,291 $3,006 $3,442 $954 $1,464 $1,833 $643 $1,001 $1,288 $32,283 $18,823 $9,453
Pure Premium w/ bottom GOV Cover ofNT$1.5 billion - Other Household
$193 $253 $290 $139 $213 $267 $126 $196 $253 $3,834 $2,272 $1,172
Premium w/ additional cost (15%) $227 $298 $341 $163 $251 $314 $148 $231 $297 $4,510 $2,673 $1,378
AAL ratio of Bottom 2 bn Layer 50.87% 30.41% 16.69% 67.07% 44.36% 25.53% 69.51% 48.94% 30.28% 62.70% 40.01% 40.01%Pure Premium w/ bottom GOV Cover of 2
billion of First-Floor Household$1,645 $2,331 $2,790 $639 $1,079 $1,445 $439 $735 $1,004 $21,814 $14,071 $7,067
Premium w/ additional cost (15%) $1,936 $2,742 $3,282 $751 $1,270 $1,699 $516 $865 $1,181 $25,664 $16,554 $8,314
Pure Premium w/ bottom GOV Cover ofNT$2 billion - Other Household
$163 $231 $277 $109 $185 $247 $101 $170 $232 $3,048 $1,998 $1,031
Premium w/ additional cost (15%) $192 $272 $326 $129 $217 $291 $119 $200 $272 $3,586 $2,351 $1,212
AAL ratio of Bottom 3 bn Layer 64.23% 41.91% 24.31% 79.02% 57.69% 35.97% 79.97% 61.24% 40.99% 75.40% 53.08% 53.08%Pure Premium w/ bottom GOV Cover of 3
billion of First-Floor Household$1,198 $1,945 $2,535 $407 $821 $1,242 $288 $558 $850 $14,387 $11,005 $5,527
Premium w/ additional cost (15%) $1,409 $2,289 $2,982 $479 $966 $1,461 $339 $657 $1,000 $16,926 $12,948 $6,503
Pure Premium w/ bottom GOV Cover ofNT$3 billion - Other Household
$119 $193 $251 $70 $141 $213 $67 $129 $196 $2,010 $1,563 $806
Premium w/ additional cost (15%) $140 $227 $296 $82 $165 $250 $78 $151 $231 $2,365 $1,839 $948
S3 S7 S9 S11
Content Cover (3.3 Mill. First Floor Households) (0.37 Mill. First Floor Households)
Living Expense & Electrical & Mechanical Equipment Loss Cover-Limit of NT$ 20,000 (4.3 Mill. 2nd Floor above Households ) (0.75 Mill. Households)
Constructed Total Loss Cover-NT$120 Mill. (7.6 Mill. Households) (1.12 Mill. Households)
Premium w/o Bottom GOV Cover
Premium w/ Bottom 1 Billion GOV Cover
Premium w/ Bottom 1.5 Billion GOV Cover
Premium w/ Bottom 2 Billion GOV Cover
Premium w/ Bottom 3 Billion GOV Cover
Major Findings Government involvement is needed to increase
the amount of flood insurance in force Future Work Needed on Modeling Predictions and detection of large-scale natural disasters Integrate climate/hydrology/socio-econ database Improve flood hazard maps Collect risk mitigation/ flood exposure data Upgrade/calibrate risk assessment model Design of multi-peril assessment model
Policy Options –A Tool Box Farm Level: Diversification, insurance Add value to move away from raw product Adopt agricultural research
Supply Chain level: Add value by moving up value chain Improve food research Invest in better infrastructure New distribution methods (network v.s. hub and spoke)
Policy/Market level: Hedging options, price pooling, Food reserves Insurance tools Information (monitoring, early warning)
136
Case Study: Food Security Risk
• APEC Food Emergency Response Mechanism
• Purpose• As an Insurance
Pool for large risk
• Reduces public expenditures on expanding food reserves for natural disasters.
• Risk Assessment
CBA for Rice under Different OptionsData Source and Per Capita Consumption Target
Calculation 3-Month 2-Month 1-Month1. RiceTOTAL BENEFIT (ANNUAL) (1) Food Aid Needs in MT Table 4-6 2,662,873 1,775,098 887,624 (2) Marginal Value per MT in GDP Appendicx C-1 544.52 544.52 544.52 (3) Marginal Value per MT in Welfare Appendicx C-1 535.86 535.86 535.86 (4) Total Benefit in GDP (Mil US$) (4)= (1)*(2) 1,449.99 966.58 483.33 (5) Total Benefit in Welfare (Mil US$) (4)= (1)*(3) 1,426.94 951.21 475.65 TOTAL COST (ANNUAL) (6) Market Price per MT Appendix C-1 333.56 333.56 333.56 (7) Total Procurement Cost in Mil US$ (7)=(1)*(6) 888.22 592.09 296.07 (8) Total Adminstration Cost in Mil US$ Table 2-1 0.18 0.18 0.18 (9) Total Logistic Cost in Mil US$ (9)=(7)*0.27 239.82 159.87 79.94 (10) Total Cost (Mil US$) (10)= (6)+(7)+(8)+(9) 1,128.22 752.14 376.19 Benefit-Cost Ratio (11) in GDP (11)= (4)/(10) 1.285 1.285 1.285 (12) in Welfare (12)=(5)/(10) 1.265 1.265 1.264
• Great variety of options available to make society more resilient to climate risks
• Many components should included Private actors as well as Public policy National effort or with International cooperation
and coordination Risk reducing/sharing as well as
income/efficiency enhancing measures• Most policies require careful, critical appraisal
before being accepted• Need analytical tools• Need to collect information How to deploy and use them adequately and
effectively?
Conclusions
總計畫 評估組
環境組 治理組
謝謝聆聽
總計畫 評估組
環境組 治理組
氣候變遷調適科技整合研究計畫Taiwan integrated research program on Climate Change Adaptation Technology