| 摘要: | 水體的水位、水量資訊對於水資源管理分析是極為重要的指標，兩者變化可用於分析氣候變遷、人工建設對水體造成的影響。這些資訊傳統上需要在當地設立水文站，以取得連續且即時的觀測值。然而對於偏遠地區的水體，設置水文測站需要耗費大量時間與金錢，是不切實際的做法。本次研究區位於湄公河流域，由於水力發電的需求，東南亞各國在湄公河流域中建設了超過20個水壩。其中上游水壩的水位及水量變化資訊並沒有公開，且下游水文站亦只提供近幾年的資料。有當地報導指出上游水壩的興建可能造成下游地區乾旱加劇，因此在湄公河流域中需要一種針對流域尺度且持續的監測方法，以面對未來氣候變遷觀測需求。本研究使用衛載感測器對上游小灣壩、景洪壩與下游四個檢查點進行觀測，分析水壩蓄水是否確實造成下游水資源的變化。使用資料包括兩個雷達測高衛星(Envisat與Jason-2)、雷射測高衛星ICESat數據、Landsat-5/-7/-8光學衛星以及Sentinel-1A合成孔徑雷達影像。方法中針對光學衛星影像計算各研究區改良常態差異水體指標，由雷達/光學影像中萃取出水面積資訊，並與對應時間測高數據水位觀測值結合。藉由線性回歸求得水面積-水位之間的轉換關係。便可將所有水面積觀測值轉換為水位，並以此方式加密、延長水位觀測時間序列。另一方面，可將水面積套疊至水壩蓄水前建立的數值高程模型上，使用積分求得影像拍攝時的水壩蓄水量。同樣進行線性回歸，求得水面積-水量之間的轉換方程式。本研究方法於上游水壩觀測水位的誤差約為2-5公尺，觀測水量的誤差約百分之三。檢查點水位測量精度可達1公尺，由這些點位的水位變化可以發現水壩蓄水後濕季水位有下降趨勢(約0.32±0.14公尺/年)，乾季水位則呈現上升趨勢(約0.18±0.08公尺/年)。此現象符合前人文獻所分析的結論，應為水庫調節水流所造成。;Water level (WL) and water volume (WV) of surface-water bodies are among the most crucial variables used in water-resources assessment and management. They fluctuate as a result of climatic forcing, and they are considered as indicators of climatic impacts on water resources. Quantifying riverine WL and WV, however, usually requires the availability of timely and continuous in-situ data, which could be a challenge for rivers in remote regions, including the Mekong River basin. As one of the most developed rivers in the world, with more than 20 dams built or under construction, Mekong River is in need of a monitoring system that could facilitate basin-scale management of water resources facing future climate change. This study used spaceborne sensors to investigate two dams in the upper Mekong River, Xiaowan and Jinghong Dams within China, to examine river flow dynamics after these dams became operational. We integrated multi-mission satellite radar altimetry (RA, Envisat and Jason-2), satellite laser altimetry ICESat, Landsat-5/-7/-8 Thematic Mapper (TM)/Enhanced Thematic Mapper plus (ETM+)/Operational Land Imager (OLI) optical and Sentinel-1A synthetic aperture radar (SAR) remote sensing (RS) imageries to construct composite WL time series with enhanced spatial resolutions and substantially extended WL data records. An empirical relationship between altimetry WL and water extent was first established for each dam and 6 checkpoints, and then the combined long-term WL time series from Landsat/Sentinel-1A images are reconstructed for all study sites. The R2 between altimetry WL and Landsat water area measurements is >0.9. Next, the Tropical Rainfall Measuring Mission (TRMM) data were used to diagnose and determine water variation caused by the precipitation anomaly within the basin. Finally, the impact of hydrologic dynamics caused by the impoundment of the dams is assessed. The discrepancy between satellite-derived WL and available in-situ gauge data, in term of root-mean-square error (RMSE) is at 2–5 m level at upstream dams, and 1 m at downstream checkpoints. Estimated WV variations derived from combined RA, RS imageries and shuttle radar topography mission (SRTM) data are consistent with results from in-situ data with a difference at about 3%. We concluded that the river level downstream is affected by a combined operation of these two dams after 2009, which has increased WL by 0.18±0.08 m•yr-1 in dry seasons and decreased WL by 0.32±0.14 m•yr-1 in wet seasons. |
