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  1. NTU Theses and Dissertations Repository
  2. 生物資源暨農學院
  3. 農藝學系
Please use this identifier to cite or link to this item: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/97219
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???org.dspace.app.webui.jsptag.ItemTag.dcfield???ValueLanguage
dc.contributor.advisor劉力瑜zh_TW
dc.contributor.advisorLi-Yu Daisy Liuen
dc.contributor.author林家安zh_TW
dc.contributor.authorChia-An Linen
dc.date.accessioned2025-02-27T16:43:55Z-
dc.date.available2025-02-28-
dc.date.copyright2025-02-27-
dc.date.issued2025-
dc.date.submitted2025-02-14-
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/97219-
dc.description.abstract本研究利用廣義概似不確定性估計法 (Generalized Likelihood Uncertainty Estimation, GLUE) 對 DeNitrification-DeComposition (DNDC) 模型進行校正,以模擬 2023 年在安康農場種植的二期作水稻試驗的產量與溫室氣體排放量。研究以敏感度分析探討參數與感興趣的模擬值之間的關係,並挑選出對模擬值敏感的參數,包括作物相關參數 (如最大產量與積溫) 及土壤參數 (如有機碳含量與孔隙率)。
研究結果顯示,GLUE 方法可以提升模型的準確性,也提供一種自動化且系統化的參數校正流程,可應用於 DNDC 模型的參數優化。未來研究應結合不同的氣候條件與田間數據進行校正,並採用貝式迭代方法來估計參數,以提升模型的普遍性與預測能力。
zh_TW
dc.description.abstractThis study uses the Generalized Likelihood Uncertainty Estimation (GLUE) method to calibrate the DeNitrification-DeComposition (DNDC) model, simulating the yield and greenhouse gas emissions of the second-cropping rice experiment conducted at the AnKang Farm in 2023. Sensitivity analysis was employed to explore the relationship between parameters and the simulation values of interest, identifying the parameters that are sensitive to the simulation outcomes, including crop parameters (e.g., maximum yield and growing degree days) and soil parameters (e.g., organic carbon content and porosity).
The results demonstrate that the GLUE method not only improves the accuracy of model simulations but also provides an automatic and systematic parameter calibration process, which could be applied to optimize DNDC model parameters. Future studies should incorporate different climate conditions and field data for calibration and adopt Bayesian iterative methods to estimate parameters, thereby enhancing the model’s generalizability and predictive capability.
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dc.description.tableofcontents口試委員審定書 i
致謝 ii
摘要 iii
Abstract iv
目次 v
圖次 vii
表次 viii
縮寫列表 ix
第一章 前言 1
1.1 全球暖化因應 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 機制模型 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 DeNitrification-DeComposition . . . . . . . . . . . . . . . . . . . . . 3
1.4 敏感度分析 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4.1 局部敏感度分析與全域敏感度分析 . . . . . . . . . . . . . . . . 6
1.4.2 一次一因子法與一次全因子法 . . . . . . . . . . . . . . . . . . . 6
1.5 校正 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.6 論文架構與目標 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
第二章 材料與方法 10
2.1 試驗地點與田間資料 . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.2 DNDC 模型參數與輸入資料 . . . . . . . . . . . . . . . . . . . . . . 11
2.3 敏感度分析 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.3.1 一次一因子法 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.3.2 共慣量分析 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.3.3 參數抽樣 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.4 校正 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.4.1 概似不確定性估計 . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.4.2 校正參數 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.5 統計分析 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
第三章 結果 21
3.1 敏感度分析 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
3.1.1 一次一因子法 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
3.1.2 共慣量分析 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
3.2 概似不確定性估計 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
第四章 討論 34
4.1 敏感度分析 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
4.1.1 一次一因子法 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
4.1.2 共慣量分析 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
4.1.3 敏感參數 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
4.2 概似不確定性估計 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
4.2.1 參數先驗分布與參數估計 . . . . . . . . . . . . . . . . . . . . . . 37
4.2.2 概似函數的選擇 . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
4.3 資料收集 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
4.4 未來展望 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
第五章 結論 44
參考文獻 45
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dc.language.isozh_TW-
dc.subject敏感度分析zh_TW
dc.subject溫室氣體zh_TW
dc.subject水稻zh_TW
dc.subject校正zh_TW
dc.subject廣義概似不確定性估計zh_TW
dc.subjectDNDCzh_TW
dc.subjectcalibrationen
dc.subjectGLUEen
dc.subjectsensitivity analysisen
dc.subjectDNDCen
dc.subjectgreenhouse gasen
dc.subjectriceen
dc.title利用廣義概似不確定性估計法校正 DNDC 模式zh_TW
dc.titleCalibrating the DeNitrification-DeComposition Model Using Generalized Likelihood Uncertainty Estimationen
dc.typeThesis-
dc.date.schoolyear113-1-
dc.description.degree碩士-
dc.contributor.oralexamcommittee蔡欣甫;蔡育彰;王尚禮zh_TW
dc.contributor.oralexamcommitteeShin-Fu Tsai;Yu-Chang Tsai;Shan-Li Wangen
dc.subject.keywordDNDC,敏感度分析,廣義概似不確定性估計,校正,水稻,溫室氣體,zh_TW
dc.subject.keywordDNDC,sensitivity analysis,GLUE,calibration,rice,greenhouse gas,en
dc.relation.page50-
dc.identifier.doi10.6342/NTU202500704-
dc.rights.note同意授權(全球公開)-
dc.date.accepted2025-02-14-
dc.contributor.author-college生物資源暨農學院-
dc.contributor.author-dept農藝學系-
dc.date.embargo-lift2025-02-28-
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