| DC 欄位 |
值 |
語言 |
| DC.contributor | 水文與海洋科學研究所 | zh_TW |
| DC.creator | 童新茹 | zh_TW |
| DC.creator | Hsin-ju Tong | en_US |
| dc.date.accessioned | 2011-7-21T07:39:07Z | |
| dc.date.available | 2011-7-21T07:39:07Z | |
| dc.date.issued | 2011 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=986206002 | |
| dc.contributor.department | 水文與海洋科學研究所 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 水資源長久以來一直是人類不可或缺的資源，乾旱事件的發生在農工商產業上會因生產停頓或是減產造成經濟上的損失，也會對人民造成相當的災害與衝擊；然而乾旱無明顯之初期現象且發生的速度非常緩慢難以建立即時的預警系統，當面臨乾旱時通常最佳的決策時機已過，因此，若能在乾旱發生之前就先掌握未來水庫入流量狀況，可提早擬定對決策以降低乾旱所造成的衝擊。
目前中央氣象局提供季長期天氣展望資料，定期於每月月底發佈未來三個月逐月溫度以及雨量之機率預報，本研究的目的即在於利用此季節性預報，並透過氣象資料產生器繁衍未來三個月可能之日溫度及日雨量資料，投入水文模式中進行未來三個月石門水庫入流量之推估。
本研究利用兩種氣象資料產生器繁衍日溫度以及日雨量資料，分別為氣象資料合成模式(WGEN, Tung and Haith, 1995)與半參數氣象資料產生器(SWG, Apipattanavis et al. , 2007)，模擬結果顯示氣象資料合成模式對歷史平均值掌握度較高，而半參數氣象資料產生器對歷史平均值略微低估。將兩種氣象資料產生繁衍之日序列資料投入水文模式，結果顯示兩種氣象資料產生器在大部分模擬期間皆有掌握到未來流量的變化趨勢，但是若當月預報有不準確的情形將會影響水庫入流量模擬的準確度。
| zh_TW |
| dc.description.abstract | The water resource is indispensable for human. The occurrence of drought event would cause damage to agriculture, industry, and economy. The impact of drought is really affect people. However, drought develops slowly and imperceptibly and may remain unnoticed for a long time. So it is very hard to construct a drought early warning system. While drought coming, it is too late to make the best decision. For these reasons, if we can predict the future reservoir inflow may manage the water resource earlier and reduce the impact of drought.
The Central Weather Bureau (CWB) issued the seasonal climate forecast every month. The CWB seasonal climate forecast provide for precipitation and temperature as percentage likelihood with lead time of 3 months in 1-month moving windows. The objection of this study is to apply the product of CWB seasonal forecast, and use weather generator to derived daily weather series such as precipitation and temperature. Since the daily weather series were derived by weather generators, the 3 months inflow of Shihmen reservoir were further simulated by a physical hydrological model.
Two weather generators were selected to derived daily weather series in this study, which are weather generator (WGEN, Tung and Haith, 1995) and Semiparametric Weather Generator (SWG, Apipattanavis et al., 2007). The simulation results indicate that WGEN capture the historical mean is better than SWG. SWG shows a slight underestimate to historical mean. Use these derived daily weather series to simulate Shihmen reservoir’s inflow. The simulation results indicate that the two kinds of weather generators predicted the inflow well, but when the seasonal climate forecast is not accurate it would affect the simulation’s accuracy.
| en_US |
| DC.subject | 氣象資料產生器 | zh_TW |
| DC.subject | 石門水庫 | zh_TW |
| DC.subject | 季節性預報 | zh_TW |
| DC.subject | 乾旱 | zh_TW |
| DC.subject | Weather generator | en_US |
| DC.subject | Seasonal climate forecast | en_US |
| DC.subject | Drought | en_US |
| DC.subject | Shihmen reservoir | en_US |
| DC.title | 結合季長期天氣預報與水文模式推估石門水庫入流量 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | Linking Seasonal Climate Outlooks and Hydrological Models for Estimating Shihmen Reservoir Inflows | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |