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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Time series trends of Landsat-based ET using automated calibration in METRIC and SEBAL: The Bekaa Valley, Lebanon
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Time series trends of Landsat-based ET using automated calibration in METRIC and SEBAL: The Bekaa Valley, Lebanon

机译:使用公制和Sebal自动校准的Landsat的ET的时间序列趋势:黎巴嫩贝卡阿谷

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摘要

The Bekaa Valley in Lebanon currently hosts the highest number of refugees per capita in the world. It is also the primary agricultural production area in the country. Groundwater levels in some regions of the valley have decreased by > 15m in the last five years. Water use estimates at the regional and the field scale for this valley are crucial for enhancing resilience and for managing competing sectorial water demands. In this research, we derive a novel time series of field-scale actual evapotranspiration for the Bekaa Valley using two one-source energy balance models for the period 1984-2017, utilizing local weather data and all available original Level 1 Landsat thermal imagery and Level 2 surface reflectance products. We compare a modified METRIC model with an automated hot and cold pixel identification procedure run in batch mode to pySEBAL, a new version of SEBAL, which also has its automated anchors pixel selection algorithm. Analysis of 1200 cloud-masked and gap-filled Landsat-derived ET products show that the two models give comparable water use estimates at the seasonal and annual time steps. We estimate an average annual ET of 652 +/- 53mm (or 800 mcm) over the heavily cultivated valley in the last 34 years (with high agreement between both METRIC and pySEBAL models). Most (64%) of the ET is consumed from blue water in the dry season of May-October. ET in the wet season of November-April consumes > 70% of the precipitation in the Bekaa valley. Annual analysis shows no discernable trend in ET across the valley, but there is an increase in irrigated agriculture in the Orontes Basin in the last five years. METRIC yields 15% higher ET than pySEBAL for the non-agricultural lands in summer. A water balance analysis shows that groundwater storage in the Litani basin is decreasing at a rate of 330 +/- 50 mm yr(-1). The outcome of this research also offers unique opportunities for estimating past and future trends of groundwater withdrawals. Results can provide insights into the sustainability of irrigated agriculture and the required international interventions in the water sector for enhancing the resilience of refugee and local communities.
机译:黎巴嫩的Bekaa山谷目前在世界上举办了最多的难民人数。它也是该国的主要农业生产区。山谷的一些地区的地下水位在过去五年中减少了> 15米。区域和该谷田规模的用水估计对于增强弹性和管理竞争的持部水需求至关重要。在这项研究中,我们使用了1984 - 2017年期间的两个单源能量平衡模型,从1984 - 2017年的一个单源能量平衡模型获得了一种新的时间序列实际蒸散,利用当地天气数据和所有可用的原始级别1 Landsat热图像和水平2表面反射产品。我们将修改的度量模型与自动化的热和冷像素识别过程进行了分批模式运行的修改式度量模型,这也具有其自动锚点像素选择算法的新版本。分析1200个云掩盖和差距填充的Landsat-errived等产品表明,这两种型号在季节性和年度时间步骤提供了可比的用水估计。在过去的34年中,我们估计了在过去的耕种山谷上的平均年度ET为652 +/- 53毫米(或800 mcm)(两种公制和Pysebal模型之间的高度协议)。大多数(64%)的ET被从5月至10月旱季的大海消耗。在11月4月的潮湿季节,消耗>贝卡阿谷的降水量的70%。年度分析显示在山谷中没有任何可辨别的趋势,但在过去的五年里,奥多尔斯盆地中的灌溉农业有所增加。根据夏季非农业土地的Pysebal,等度量比Pysebal高15%。水平衡分析表明,LITANI盆地的地下水储存以330 +/- 50mm YR(-1)的速率降低。该研究的结果还提供了独特的机会,以估计过去和未来的地下水撤销趋势。结果可以为灌溉农业的可持续性以及水部门所需的国际干预措施提供洞察,以加强难民和当地社区的抵御能力。

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