| 研究生: |
蘇俊宇 Chun-Yu Su |
|---|---|
| 論文名稱: |
地表過程質傳與熱傳數值模擬 |
| 指導教授: |
李明旭
Ming-Hsu Li |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
地球科學學院 - 水文與海洋科學研究所 Graduate Instittue of Hydrological and Oceanic Sciences |
| 畢業學年度: | 94 |
| 語文別: | 中文 |
| 論文頁數: | 92 |
| 中文關鍵詞: | 土壤溫度 、土壤含水量 |
| 外文關鍵詞: | soil temperature, soil water content |
| 相關次數: | 點閱:12 下載:0 |
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本研究利用垂直整合之水文氣象站即時觀測系統觀測大氣溫度、風速風向、大氣壓力、相對濕度、降雨量、皿蒸發量、淨輻射量、太陽輻射量、土壤溫度與土壤含水量等,加上現地土樣之土壤特性分析結果與垂直一維之SHAW模式模擬,來討論地表過程之質傳與熱傳特性。主要研究方法是利用水文氣象站之微氣象觀測資料,將觀測所得之每小時氣象條件(大氣溫度、相對濕度、風速、降雨量及太陽輻射量)及初始條件(模擬初始之土壤溫度與土壤含水量),透過模式模擬土壤溫度與土壤含水量隨時間變化趨勢,並與儀器觀測之土壤含水量與溫度隨時間變化趨勢比較,對現場之土壤特性參數進行檢定及驗證,討論模式模擬結果。
模式模擬結果發現,SHAW模式對於降雨時期之表層土壤含水量變化模擬結果較好,即在接近飽和時之模擬結果較佳;模式對於表層土壤退水時期之土壤含水量變化趨勢模擬結果較差,即模式有高估的現象。由於模式僅考慮土壤特性及垂直方向上之質傳與熱傳過程,無法反應礫石土層及側向水流對土壤含水量變化趨勢之影響,故對於粗顆粒含量較高之土壤含水量模擬會有較大誤差。
以長期土壤溫度模擬結果來看,SHAW模式能有效模擬出土壤溫度長期變化趨勢,但以短期日間之模擬結果來看,對於每日中午地表溫度有高估的現象。
This study used a vertically integrated hydrological and meteorological real-time monitoring system to observe the air-temperature, wind speed and direction, air-pressure, relative humidity, precipitation, pan-evaporation, net radiation, solar radiation, soil temperature and soil moisture at the NCU meteorological site. We used those meteorological data and in situ soil characteristics to run the SHAW model and discussed the results of mass and thermal fluxes of land processes at this site.
With the given initial conditions (soil temperature and water content) and the hourly weather conditions (air-temperature, wind speed, relative humidity), the SHAW model can simulate diurnal variations of soil moisture and temperature. During rainfall periods, the saturation of soil moisture can be simulated by the model as a result of infiltration. For the recession period of soil moisture, after rainfalls cease, the discrepancies between simulated and observed soil moistures are getting larger along with the increase of simulation time.
The long-term trend of most soil temperature can be fairly described by the model, but the simulated surface temperature is higher than observed data at midday.
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