整合遙測技術、大氣環流模式與Markov模式推估未來集水區流量之研究－以淡水河集水區為例

Integrating Remote sensing techniques, GCMs model, and Markov model to estimate future stream flow: A Case Study on the Dan-Shui Watershed

吳治達(Chih-Da Wu) ； 鄭祈全(Chi-Chuan Cheng) ； 羅漢強(Hann-Chung Lo) ； 陳永寬(Yeong-Kuan Chen)

《航測及遙測學刊》 14卷1期 (2009/03) Pp. 37-50

https://doi.org/10.6574/JPRS.2009.14(1).4

摘要

環境變遷與集水區水文循環為目前國內外環境規劃與經營管理的重要議題，如何有效地監測與模擬兩者的關係亦成為該議題之重要研究課題。本研究旨在整合遙測技術、大氣環流模式(General circulationmodel; GCMs)與Markov模式，供探討氣候變遷及土地使用變遷對於淡水河集水區水文特性之影響，並比較不同GCMs 模式模擬未來河川流量的差異。研究方法首先利用混合式影像分類法進行1995年及2002年淡水河集水區之土地使用分類，並將試區分為森林、建地、水體、耕作農地及無耕作農地5個類型；其次，以兩時期之土地使用資料為基礎，應用Markov 模式預測未來短、中、長期的土地使用變遷、並推估其蒸發散覆蓋係數，結果指出，建地面積由1995年的17.71%和2002年的20.17%，增加為2030年的40.24%，2058年的48.91%及2086年的58.16%，而蒸發散覆蓋係數由1995年的0.726和2002年的0.704，下降為2030年的0.558，2058年的0.478及2086年的0.408。最後，整合GWLF水文模式和CGCM1及HADCM3兩種氣候變遷情境模式，並進行流量模擬，供評估淡水河集水區可能遭遇之影響與衝擊，結果顯示，不論在何種氣候情境下，由於建地增加和蒸發散覆蓋係數下降之影響，淡水河集水區之月流量、月平均流量及年總流量在未來短期、中期及長期之模擬結果均有變化，並將造成該集水區未來洪水發生頻率之上升。

關鍵字

遙感探測 ； 大氣環流模式 ； Markov模式 ； 土地使用變遷 ； 氣候變遷

並列摘要

Considerable attention has been given for monitoring and simulating the impacts of global environment change on forest watershed hydrology. Therefore, the purpose of this study is to integrate the remote sensing techniques, the general circulation models(GCMs), and the Markov model to investigate the effects of land use change and climate change on the Dan-Shui watershed, moreover, to compare the difference of stream flow simulations under various GCMs scenarios(i.e., CGCM1 and HADCM3).The processes were as follows: Land-use maps of the Dan-Shui watershed were firstly generated using hybrid classification and Landsat-5 images in 1995 and 2002. The study area was classified into 5 land-use types. They are forest-land, building, farm-land, baring farm-land, and water body. Secondly, the Markov model built based on those land-use data was applied to predict future land-use changes, furthermore, the generated results were used to estimate the cover coefficients (CV) of evapotranspiration based on future conditions and the GWLF water balance model. Results from the Markov prediction indicated that the area of building increased from 17.71% in 1995 and 20.17% in 2002 to 40.24% in 2030, 48.91% in 2058, and 58.16% in 2086. In addition, the estimations of the CV showed that the value decreased gradually from 0.726 and 0.704 to 0.558, 0.478 and 0.408. Finally, the GWLF model was integrated with the Markov predictions to analyze the influence of future land-use changes and climate changes on stream flow simulation under the CGCM1 and HADCM3 scenarios, and also to assess the impacts on the watershed. The results indicated that, due to the increase of building area and the decrease of the CV value, monthly stream flow, monthly average stream flow, and annual total stream flow all changed under two climate change scenarios, regardless of the short-, middle- or long-term simulation,. Furthermore, land-use changes and climate changes would lead to increase the occurrences of floods.

並列關鍵字

Remote sensing ； General circulation model ； Markov model ； Land-use change ； Climate change