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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 童慶斌(Ching-Pin Tung) | |
dc.contributor.author | Tzu-Chun Chang | en |
dc.contributor.author | 張慈純 | zh_TW |
dc.date.accessioned | 2023-03-19T23:36:02Z | - |
dc.date.copyright | 2022-09-26 | |
dc.date.issued | 2022 | |
dc.date.submitted | 2022-09-13 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/86083 | - |
dc.description.abstract | 水資源是企業的根本,貫穿於生產與營運的過程中。隨著近年來對於水風險與水管理的意識提升,水資源逐漸成為企業與投資人關注的焦點,並且在氣候變遷的壓力下,氣候相關風險的評估與揭露已經成為趨勢。然而企業在面對水相關風險的評估時,仍面臨著缺乏正確且適合的資訊或方法等挑戰,導致企業在進行水相關風險評估時躊躇不前。現今企業實務上普遍使用水風險相關工具,如世界資源研究所(WRI)開發的Aqueduct,也僅限於水風險的識別,無法實現風險量化,亦不足以作為企業管理的基礎。因此,為使企業能夠全面評估水相關風險,本研究建立完整的企業水風險評估框架,配合不同時間尺度的設計,協助企業掃描與量化水風險,作為企業的參考指引。 此企業水風險評估框架通過四個步驟:價值鏈重大性評估、辨識水相關風險與機會、評估量化水相關風險以及最後的企業回應完善企業水管理流程。其中第三步驟因涉及風險量化對於企業最具困難度,本研究選用企業間關注度較高的缺水風險,以高產值且高耗水的半導體製造業作為案例研析應用於步驟三並將評估結果延伸至步驟四協助企業回應。缺水風險量化使用中央氣象局季長期天氣展望與氣候情境相關資料,透過全球氣候模型降尺度、氣象合成模式、GWLF水文模式與水資源系統動力模式實現一至三個月季長期缺水風險預警與氣候變遷下缺水風險評估,做為區域供水對於廠區的影響,並以水情燈號鏈結廠區缺水風險。廠區的部分利用本研究建置之廠房水資源系統動力模式並採用回復力、可靠度、脆弱度等三項風險指標探討供水系統的供水能力與調適選項的選擇。整體評估方法具有合理性,評估結果對於廠區具有參考價值,透過此框架使企業的布局能因應現況水風險並避開氣候變遷可能帶來的水風險,進而在CDP、DJSI等國際評級中獲得優良表現。 | zh_TW |
dc.description.abstract | Water resource is the foundation of enterprise, running through the process of production and operation. With the increasing awareness of water risk and water management in recent years, water resources have gradually become the focus of enterprises and investors. Under climate change, assessing and disclosing climate-related risks have become a trend. However, the challenges faced by enterprises in water-related risk assessment include the lack of correct and appropriate information or methods, which leads to the hesitation of enterprises in water-related risk assessment. Aqueduct, developed by the World Resources Institute (WRI), is a widely used water risk assessment tool for enterprises, limited to identifying water risks. It cannot achieve quantifying and is insufficient to serve as a basis for enterprises to respond. Therefore, to enable enterprises to capture water-related risks fully, this study established a water risk assessment framework with different time scales. This water risk assessment framework improves enterprises’ water management through four steps: Value chain water materiality assessment, Identifying water-related risks and opportunities, Evaluating and quantifying water-related risks, and Enterprise response. The third step involves risk quantification, which is the most difficult part. This study selected water shortage risk and took the semiconductor manufacturing industry with high output value and high water consumption for a case study, and extended results to the fourth step. Water shortage quantification used seasonal weather outlook and climate scenarios data, downscaling, weather generation, GWLF hydrological model and water resource system dynamic model to realize seasonal early warning and water risk assessment under climate change. The water supply of plant would be directly affected by regional water supply monitoring index. For the plant part, this study built a water resource system dynamic model of plant and used three risk indicators, namely resilience, reliability and vulnerability to assess water supply capacity and sort adaptations. In conclusion, the assessment is reasonable and the result has reference value for plant. With this framework, enterprises can perfectly respond to current water risks and avoid the water risks caused by climate change, thus achieving good performance in international ratings such as CDP and DJSI. | en |
dc.description.provenance | Made available in DSpace on 2023-03-19T23:36:02Z (GMT). No. of bitstreams: 1 U0001-0909202213325000.pdf: 6822425 bytes, checksum: 7c67cb408b00b5c4465feacb45c457f4 (MD5) Previous issue date: 2022 | en |
dc.description.tableofcontents | 誌謝 i 摘要 ii ABSTRACT iii 圖目錄 viii 表目錄 xi 第一章 緒論 1 1.1 研究動機 1 1.2 研究目的 2 1.3 論文框架 3 第二章 文獻回顧 5 2.1 氣候變遷對區域水資源的影響 5 2.1.1 氣候變遷風險定義 5 2.1.2 台灣水資源現況 7 2.1.3 氣候變遷對台灣水資源的衝擊與評估方法回顧 8 2.2 企業水風險管理 10 2.2.1 企業水風險 11 2.2.2 水風險管理、評估流程與範疇界定 12 2.3 半導體廠房水資源系統 14 2.3.1 工業用水分類 14 2.3.2 半導體廠房用水特性 16 2.3.3 半導體廠房用水流程 17 2.3.4 工廠水平衡 18 2.3.5 用水效率指標 21 第三章 研究方法 22 3.1 水風險評估框架與相關工具 22 3.1.1 企業水風險評估框架 22 3.1.2 企業實施水風險管理的參考依據 24 3.2 辨識水相關風險與機會 27 3.2.1 標準化降雨指標 27 3.2.2 水情燈號 28 3.2.3 乾旱脆弱度 31 3.2.4 台灣地區未來情境下水情地圖 32 3.3 評估量化水相關風險 33 3.3.1 中央氣象局季長期天氣展望 35 3.3.2 氣候情境 36 3.3.3 全球氣候模型降尺度 38 3.3.4 氣象合成模式 39 3.3.5 GWLF水文模式 40 3.3.6 水資源系統動力模式 44 3.3.7 缺水風險指標 47 第四章 應用案例研析 48 4.1 應用案例設計 48 4.1.1 案例廠房水平衡圖 48 4.1.2 廠房水資源系統動力模式 49 4.2 一至三個月季長期缺水風險預警 54 4.2.1 歷史氣象資料選用 54 4.2.2 基於完美預報之水情燈號推估 56 4.2.3 實際燈號與蓄水量燈號比對校正 60 4.2.4 缺水風險預警 62 4.2.5 GWLF模式與桃園水資源系統動力模式驗證 64 4.3 氣候變遷下缺水風險評估 67 4.3.1 情境設定與模式選擇 67 4.3.2 氣候變遷情境下之水情燈號推估 69 4.3.3 氣候變遷對於桃園地區的供水影響 72 4.3.4 氣候變遷下廠區缺水風險評估 74 4.4 企業回應 77 4.4.1 廠區缺水應變 77 4.4.2 辨識與評估調適選項 81 4.4.3 水風險評估框架與國際評級的回應 85 第五章 結論與建議 91 5.1 結論 91 5.2 建議 95 第六章 參考文獻 97 | |
dc.language.iso | zh-TW | |
dc.title | 建立企業廠區水風險評估框架與應用於缺水風險評估 | zh_TW |
dc.title | Establishment of Water Risk Assessment Framework for Enterprises and Application to Water Shortage Risk Assessment | en |
dc.type | Thesis | |
dc.date.schoolyear | 110-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 李明旭(Ming-Hsu Li),謝宜桓(Yi-Huan Hsieh),許少瑜(Shao-Yiu Hsu) | |
dc.subject.keyword | 乾旱,缺水風險,廠房,企業,氣候變遷,水資源, | zh_TW |
dc.subject.keyword | Drought,Water shortage risk,Plant,Enterprise,Climate change,Water resource, | en |
dc.relation.page | 100 | |
dc.identifier.doi | 10.6342/NTU202203261 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2022-09-13 | |
dc.contributor.author-college | 理學院 | zh_TW |
dc.contributor.author-dept | 氣候變遷與永續發展國際學位學程 | zh_TW |
dc.date.embargo-lift | 2022-09-26 | - |
顯示於系所單位: | 氣候變遷與永續發展國際學位學程(含碩士班、博士班) |
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