量測沙奇盤深度為量化水體澄清度(透明度)最直接且快速的方式，也是優養判定的指標之一。國內被判定為優養化之水庫大多都是透明度太低，而改善透明度要從何種污染物著手卻僅仰賴透明度與水質的經驗關係，以卡爾森經驗式為例，若根據該式建議藉由改善葉綠素a來提高國內水庫的透明度，恐怕大多數水庫都無法得到令人滿意的結果。因此，本研究利用水體光學理論、水庫生光特性分析資料及最佳化方法，建立最適合國內22座水庫之透明度物理模式，以能準確解析水中光敏物質濃度、環境光場與透明度間的關係。此外，透過2005至2013年共2400筆國內水庫觀測資料與最佳化，本研究嘗試找出透明度物理模式中兩個主要衛星影像參數(光衰減係數與遙測反射率)的最適波段，並運用在Landsat 8跟Sentinel 2A兩個中解析度衛星影像上，比較兩個影像資料，並探討遙測透明度與其他水質的關係。
在建立水庫透明度物理模式方面，本研究建立一套半解析透明度(SA-SD)模式，其模式中包含了生光模式、輻射傳輸模式、準解析模式和新透明度物理模式，輸入過去環保署十年大量的水庫水質採樣資料，選出生光模式中九個係數為決策變數：(1) 以線性迴歸模式連結懸浮固體物濃度(SS)與無機顆粒吸收係數adm(400)、連結總溶解性有機碳(TOC)與有色溶解性有機物質(CDOM)吸收係數ag(440)，以及以SS連結總顆粒背向散射係數bbp(550)之6個迴歸係數；(2) 無機顆粒和CDOM吸收光譜斜率常數的 S_dm和S_g，以及(3) 總顆粒背向散射光譜指數常數。其次，利用基因演算法將SA-SD模式最佳化，率定出最佳生光係數解。經過訓練及驗證之SA-SD模式，其準確性可達log-R2=0.73，比較卡爾森的透明度與葉綠素a回歸關係式，還有以現地資料進行多元迴歸分析方法所推導的關係式，log-R2值分別為0.07與0.71，結果顯示本研究之SA-SD模式比一般的回歸關係式有較高的準確度。此外以最佳綠光波段解析水庫透明度也比Z. Lee et al. (2015)提出以藍光波段為佳。SA-SD模式敏感度分析結果顯示SS與TOC為主要影響透明度的變數，且模式唯一限制條件是不能接受葉綠素a濃度為零。
在以Landsat 8跟Sentinel 2A衛星影像遙測國內水庫透明度方面，本研究發現半解析模式中輻照度漫射衰減係數(Kd)及水面輻射反射率(rw)在Landsat 8影像應採用561波長，在Sentinel 2A影像應採用560波長，此與過去Z. Lee et al. (2015)發展此透明度模式應用於海洋水體採用之490波長有所不同。Landsat 8和Sentinel 2A影像分別具有30及10公尺解析度，雖比不上過去國內水庫常用之SPOT (10 m)與福衛二號影像(8 m)，但仍能顯示蓄水面積最小主要水庫的水質變化，且具有免費、品管嚴謹、能進行嚴謹大氣校正、多頻譜及光譜解析度較高的優勢。比較Landsat 8和Sentinel 2A資料於水庫水質遙測之運用，Sentinel 2A衛星對於透明度較高之水庫，如翡翠及日月潭水庫，有較高的失真率；但對於較低透明度且面積小之澄清湖水庫，則有不錯的解析能力；而在Landsat 8部份，對於各水庫透明度的分佈情形皆能精確掌握，較具有台灣水庫透明度遙測之可行性。故以Landsat-8影像分析國內8座主要水庫水質，透明度與濁度分佈有密切關係，受到沿岸及入流口沖刷的影響，帶來的懸浮物質造成透明度較低；另外，由於集水區的營養鹽排入水庫中，所以在相對透明度較高的地方，受到的光穿透較深造成藻類大量生長，而有較高的葉綠素a濃度。
本研究建議以半解析模式分析水質與透明度的關係，有科學根據性地找出造成水庫透明度惡化的主要原因，並能對症下藥改善水質。為提高SA-SD的實用性，未來應將模式中bbp()項細分出針對藻體顆粒背向散射係數bbph()項，以進一步探討藻體顆粒對透明度的影響。經本研究評估Landsat-8最適合用於國內水庫水質遙測，就透明度而言其遙測水質相對差異百分比為25 %，其他水質(葉綠素a及濁度)準確度雖不在本研究探討之列，但分析透明度與其他水質間的空間變化關係，發現透明度的分佈主要與濁度有關。另外，分析透明度與葉綠素a間關係，可將八座水庫分為：(1) 以光為限制因子之A類；(2) 以營養鹽為限制因子之B類；(3) 混合光及營養鹽為限制因子之C類。針對不同分類，可以了解營養鹽類及光穿透水體對藻類生長的影響，藉此擬訂不同改善水庫優養化之計畫。
因此，本研究認為利用Landsat 8針對透明度與其他水質之間的比較，具有能即時掌握水庫水質的受損情況及污染來源的能力，建議相關管理機關可將其納為監測水庫全域水質的平台。

The measurement of Secchi disk depth to quantify the clarity (transparency) of water is the most direct and fast way, and most of reservoirs in Taiwan which was identified as the eutrophic reservoir because of low transparency. Transparency must be based on science as the background combined the water optical theory and physical model of transparency to explore the impact of domestic reservoir transparency of the key factors.
Therefore, this study was corrected the semi-analytical transparency (SA-SD) model to figure out optimum decision variables by using genetic algorithm. After the pattern verification, the log-R2 is 0.73, and drew a comparison between Carlson's experimental algorithm, and the stepwise regression, the log-R2 is 0.07 and 0.71, respectively. The results showed that the SA-SD model of this study have higher accuracy than the general regression models.
The remote sensing of inland water body mostly through the empirical relationship method of measuring the transparency in the past. In this study the results found that the domestic reservoir of radiative attenuation coefficient (Kd) and the surface radiation reflectance (rw) which tr and pc wavelength are located in the green band. So this study attempts to use Landsat 8 and Sentinel 2A high resolution multispectral satellite images, using green band Kd and rw as input product through the new transparent physical model for mapping Secchi disk depth of eight reservoirs.

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