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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 黃誌川 | |
| dc.contributor.author | Chiao-Ying Lan | en |
| dc.contributor.author | 藍巧穎 | zh_TW |
| dc.date.accessioned | 2021-06-17T03:11:09Z | - |
| dc.date.available | 2021-07-23 | |
| dc.date.copyright | 2018-07-23 | |
| dc.date.issued | 2018 | |
| dc.date.submitted | 2018-07-17 | |
| dc.identifier.citation | Akaike, H. (1974) A new look at the statistical model identification, IEEE Transactions on Automatic Control: 716 - 723.
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/69238 | - |
| dc.description.abstract | 河水平均通過時間 (MTT) 和新水比例 (Qe%) 可分別用以描述集水區中的水文途徑和逕流來源。然而，MTT和Qe% 的估算卻少被用來探討於副熱帶山區，尤其是極端降雨的事件尺度下。本研究應用轉換函數水文分離模式(TRANSEP) 來估算颱風降雨事件中台灣北部坪林集水區 (集水面積: 5-195 km2) 的MTT和Qe%，並測試TRANSEP模式中的四種機率分布模式 (TTD) (珈瑪分布、指數型分布、線性水庫分布、離散型分布)，結果發現 (1)由流量和δ18O追蹤劑的模擬結果中，指數型分布(EXP)的模擬表現分別可高達NSE:0.90和NSE:0.87，指數型分布(EXP)意味著此地區的水文作用主要是均勻混合的水流特性。(2) MTT結果大約是2.8至5.5小時且Qe%範圍在19%至29% 之間，表示著雨水轉換成為逕流的過程相當迅速。(3) 平均高程、集水區周長、平均坡度為控制台灣坪林集水區的MTT (R2: 0.99)的重要地景特性，但還未呼應到全球尺度的集水區，可能受到水流過程的複雜性所致。(4) 無論是地區或全球尺度下，Qe%的模擬結果可良好的被地景特性解釋(R2= 0.83)，並且再次的驗證地形起伏越大的地景特性下，較不利於事件水的產生。 | zh_TW |
| dc.description.abstract | Mean transit time (MTT) and event water ratio (Qe%) are determinants of biogeochemical cycle. However, MTT and Qe% in subtropical montane catchments are rarely discussed, particularly during typhoon invasions. In this study, the transfer function hydrograph separation model (TRANSEP) embedded with 4 TTDs (GM, EXP, TPLR, DM) was applied to estimate MTTs and Qe% in 5 catchments (5-195 km2) in Ping-Lin, Taiwan during a storm event. Results showed that (1) the EXP model outperformed other three TTDs, which can simulate runoff and δ18O tracer with high NSE of 0.90 and 0.87, indicating a well-mixed behavior during typhoon invasion; (2) the MTTs (2.8-5.5 hours) and the Qe% (19-29%) demonstrated quick conversion from rainfall to streamflow; (3) locally, the mean elevation, perimeter and mean slope can estimate the MTT well (R2=0.99), but not for global scale, probably due to the complexity of water transport dynamic; (4) both locally and globally, Qe% can be well estimated by landscape characteristics supporting the steep landscape is unfavorable with event water generation. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T03:11:09Z (GMT). No. of bitstreams: 1 ntu-107-R05228032-1.pdf: 4396532 bytes, checksum: 09b7fda25bf8a06dfc4e7a7e411deebb (MD5) Previous issue date: 2018 | en |
| dc.description.tableofcontents | Table of contents
謝誌 II 摘要 III Abstract IV 1 Introduction 1 2. Literature Review 6 2.1 The definition of water transit time 6 2.2 Hydrograph separation for event water ratio (Qe%) 7 2.3 Evaluation of Mean transit time 10 2.4 Controlling factors of MTT: landscape characteristics 14 3 Material and methods 17 3.1 Site description 17 3.2 Isotopic Analysis- Isotopic Water Analyzer 20 3.3 Transit time model- TRANSEP 24 3.3.1 Model description 24 3.3.2 Model performance and the model selection 29 3.4 Topographic analysis 31 3.5 Multiple linear regression (MLR) 33 4. Result 36 4.1 Water Isotopic Composition in Precipitation and Streamflow 36 4.2 Model selection and Best-fitted simulation 41 4.2.1 TTDs identification: AIC evaluation and hydrograph simulation 41 4.2.2 The estimation of MTT and Qe % 51 4.2.3 Isotopic hydrograph separation 52 4.3 Correlations of MTT with landscape characteristics 53 4.3.1 Landscape characteristics in Ping-Lin region 53 4.3.2 Relationship of MTT and landscape characteristics 55 4.3.3 Relationship of Qe% and landscape characteristics 60 5. Discussion 64 5.1 Model selection of TTDs 65 5.2 MTTs estimation derived from landscape characteristics 66 5.3 Qe% estimation derived from landscape characteristics 68 6. Conclusion and Suggestion 71 References 73 Appendix A The correlation matrix between landscape characteristics and soil property. (The Black bold shows the collinear between the two parameters) 79 Appendix B The local meteoric water line (LMWL) in Ping-Lin. The precipitation data were sorted with different time period (winter season, summer season and Saola typhoon event). 80 Appendix C Uncertainty of the model simulation on MTT and event water discharge. 81 Appendix D The test for multi-collinear on landscape characteristics for MTT 83 Appendix E All the permutation combination of landscape characteristics for the linear regression model of MTT. 85 Appendix F The test for multi-collinear on landscape characteristics for Qe% 86 Appendix G The observation data in PL catchment during Saola typhoon event. 88 | |
| dc.language.iso | en | |
| dc.subject | 通過時間分布 | zh_TW |
| dc.subject | 河水平均通過時間 | zh_TW |
| dc.subject | TRANSEP 模式 | zh_TW |
| dc.subject | 同位素追蹤劑δ18O | zh_TW |
| dc.subject | 地形特徵 | zh_TW |
| dc.subject | δ18O isotopic tracers | en |
| dc.subject | transit time distribution | en |
| dc.subject | landscape characteristics | en |
| dc.subject | mean transit time | en |
| dc.subject | TRANSEP model | en |
| dc.title | 河水平均通過時間和新水比例與地景特性的關聯 | zh_TW |
| dc.title | Linking landscape characteristics to the stream mean transit time and event water ratio on subtropical montane catchments | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 106-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 彭宗仁,李宗祐 | |
| dc.subject.keyword | 河水平均通過時間,TRANSEP 模式,同位素追蹤劑δ18O,地形特徵,通過時間分布, | zh_TW |
| dc.subject.keyword | mean transit time,TRANSEP model,δ18O isotopic tracers,landscape characteristics,transit time distribution, | en |
| dc.relation.page | 90 | |
| dc.identifier.doi | 10.6342/NTU201801559 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2018-07-18 | |
| dc.contributor.author-college | 理學院 | zh_TW |
| dc.contributor.author-dept | 地理環境資源學研究所 | zh_TW |
| 顯示於系所單位： | 地理環境資源學系 | |
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