以模式推估淹水範圍與深度已相當普及，而淹水模擬演算中，淹水區位之曼寧粗糙係數空間分布顯著影響模擬結果。傳統曼寧粗糙係數之配置，多以土地利用為基準，由參考手冊或前人研究資訊給予適當的曼寧粗糙係數值，但地覆類別曼寧粗糙係數值變異極大，導致係數難以客觀給定。地表植生多寡顯著影響土壤入滲與地表糙度，可有效的用於推算曼寧粗糙係數，以植生指標可反映地表植生量，藉由植生指標轉換推求地覆曼寧粗糙係數之空間分布，取代傳統查表給定之配置方式為本研究之重點。
以後龍溪易淹水潛勢河段為研究試區，運用SPOT衛星影像萃取植生指標配置淹水區位曼寧粗糙係數，配置類型分為線性配置Ⅰ、線性配置Ⅱ、乘冪配置與多項式配置，以網格間距80公尺、60公尺、40公尺及30公尺配置試區，採用FLO-2D模式進行模擬並與傳統土地利用配置方式進行比較，評估其可行性並分析討論。
經模擬結果顯示，網格80公尺各配置類型模擬結果與傳統配置結果差異不大，而網格60公尺、40公尺與30公尺時線性配置模擬結果明顯與傳統配置結果不符，其淹水範圍與深度均有低估現象，且模擬結果會隨網格間距而變動，淹水範圍相似度變動幅度高達31.3%；淹水深度相對誤差變動幅度約為53.6%。而以乘冪、多項式配置有較佳模擬結果，其可行性評估淹水範圍相似度、相似率均高達95%左右，淹水深度相對誤差均低於10.7%以下，且模擬結果不受網格間距而變動，較適用於模擬及配置上，故可有效地萃取淹水區位之曼寧粗糙係數供淹水模擬之用。It has already been very popular nowadays to use the models for simulating the inundation area and water depth. The spatial distribution of Manning's roughness coefficient (Manning's n value) at the inundation areas significantly affects the results of simulation. Traditionally, the proper Manning's n value for a given area is directly derived from land use data recommended by the user manual and/or the previous studies. Due to highly variations in the Manning's n value recommended from the reference manuals and/or previous study at the same condition of land use, it's difficult to give the suitable Manning's n values to fit in with the variation of land cover. Because vegetation significantly affects infiltration and roughness of ground surface, vegetation index can be used to calculate and display the spatial distribution of Manning's n value.
This study focuses on the possibility of extracting the spatial distribution of Manning's n value form vegetation index, which is calculated from the remote sensed imagery. Regression equation such as: Linear transformation(Ⅰ), linear transformation(Ⅱ), power regression, and polynomial regression are used to understand the relationship between Manning's n value and vegetation index. Different grid sizes (80m, 60m, 40m, and 30m) of the digital terrain model are also employed to simulate the inundation area in holun river watershed by using FLO-2D model for discussing the feasibility of Manning's n value extracted from vegetation index.
Results show that there is no significant difference in the areas and depths of inundation simulation for the grid size 80m at different treatments. For the grid size 60m, 40m, and 30m, there is a significant difference between treatment of linear transformation and traditional methods, the treatment of linear transformation showing underestimation in both the areas and depths of inundation and the results varies with grid size change. The variation of similarity for the simulation of inundation areas is up to 31.3%, and the relative error for the simulation of inundation depth is 53.6%. The treatments of power regression, polynomial regression with 95% similarity in inundation area and with less than 10.7% of relative error in inundation depth, which showing better performance no matter how the grid size change. It means that treatments of power regression and polynomial regression can be applied to extract the spatial distribution of Manning's n value for the use of inundation simulation.摘要 I
ABSTRACT II
目錄 IV
表目錄 VI
圖目錄 VIII
壹、前言 1
貳、前人研究 2
一、 植生指標相關應用 2
二、 土地變遷對逕流之影響 3
三、 水文分析相關研究 4
(一) 平均雨量 4
(二) 設計雨型 5
(三) 頻率與歷線相關研究 7
四、 淹水模擬相關研究 8
五、 曼寧粗糙係數 10
參、研究材料與方法 13
一、 試區概述 13
二、 研究架構及流程 14
三、 研究材料 15
(一) 地文資料 15
(二) 水文資料 15
四、 研究方法 20
(一) 水文分析 20
(二) 植生指標 30
(三) 土地利用 31
(四) 曼寧粗糙係數 31
(五) 淹水模擬 39
肆、結果與討論 44
一、 模擬結果 44
(一) 網格80公尺淹水範圍 44
(二) 網格60公尺淹水範圍 46
(三) 網格40公尺淹水範圍 49
(四) 網格30公尺淹水範圍 51
二、 可行性分析 54
(一) 淹水範圍 54
(二) 淹水深度 56
(三) 綜合結果 58
伍、結論與建議 62
一、 結論 62
二、 建議 63
陸、參考文獻 6
