臺灣博碩士論文加值系統

近年來全球受極端天氣與氣候事件影響，災害規模不斷擴大，災害頻率也急速攀升，對於氣候變遷與極端事件的不確定性與風險，若能由早期被動之搶救作業，提升為主動之資訊分析研判與提早有效的預警模式，未雨綢繆事先作好預測，期能有效預防及降低災害損失。
本研究以高屏溪流域中之高屏溪攔河堰內濁度(turbidity)日變化為例，運用年平均、年標準差、標準差、偏態係數及自相關係數，將監測數據作統計之時間序列分析，並觀察在莫拉克(Morakot)颱風前後水中濁度在不同時間點的變化，找出當監測值到達某一臨界轉換(critical transition, CT)的訊號，從分析證據顯示確認臨界轉換的現象為閃爍(flickering)。藉由統計分析的領先指標，在接近臨界轉換的動力特徵也證實了突然狀態改變的證據。目前的研究結果可提供相關管理單位作為後續水質變化的預警及控制之防減災因應對策參考，期使災害程度能大幅度減輕。

In recent years, extreme weather and climate events affect the world on a global scale, and the frequency and severity of natural disasters rises drastically. In the face of climate change and the uncertainty and risk of extreme events, if the passive rescue operational model can be changed to an aggressive assessment of data model for early warning, planning and predicting well in advance, we can hopefully reduce the losses from disasters.
In this study, the turbidity diurnal variation of the Gaoping River Weir in the Gaoping River basin was monitored statistically by using yearly mean, yearly standard deviation, standard deviation, skewness and autocorrelation by performing time series analysis of the recorded data. Water turbidity at different time points before and after Typhoon Morakot was also observed to find out the signals when the monitor value reaches a certain critical transition (CT), and then identify that the phenomenon of CT is flickering. Dynamic characteristics of an impending CT by leading indicators of statistical analysis are also shown for verifying the evidence of abrupt state changes. The results of the present study may provide some reference for the related regulatory agencies in management of river basins and the early warning of deteriorating water quality, on the hopes of greatly reducing the impact of disasters.

目 錄
摘要 i
英文摘要 ii
誌謝 iii
目錄 v
表目錄 vii
圖目錄 viii
第一章 前言 1
1-1 研究緣起與動機 1
1-2 研究目的 1
1-3 研究流程 2
第二章 文獻回顧 3
2-1 降雨對河川水質的影響 3
2-2 早期預警分析 5
2-2-1翻轉點的現象 5
2-2-2氣候及生態系統 10
2-2-3河川水質的預警模式 14
第三章 研究方法與步驟 18
3-1 研究方法 18
3-2 研究步驟 19
3-3 高屏溪流域簡介 21
第四章 結果與討論 24
4-1 時間序列數據處理 24
4-2 長期趨勢分析 24
4-3 預警訊號分析 29
第五章 結論與建議 38
5-1 結論 38
5-2 建議 38
參考文獻 39
附錄一 日降雨量資料 45
附錄二 濁度資料 53
附錄三 日降雨量領先指標 61

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