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首页> 外文期刊>The Science of the Total Environment >Improved remotely sensed satellite products for studying Lake Victoria's water storage changes
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Improved remotely sensed satellite products for studying Lake Victoria's water storage changes

机译：改进的遥感卫星产品，用于研究维多利亚湖的储水量变化

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Lake Victoria (LV), the world's second largest freshwater lake, supports a livelihood of more than 42 million people and modulates the regional climate. Studying its changes resulting from impacts of climate variation/change and anthropogenic is, therefore, vital for its sustainable use. Owing to its shear size, however, it is a daunting task to undertake such study relying solely on in-situ measurements, which are sparse, either missing, inconsistent or restricted by governmental red tapes. Remotely sensed products provide a valuable alternative but come with a penalty of being mostly incoherent with each other as they originate from different sources, have different underlying assumptions and models. This study pioneers a procedure that uses a Simple Weighting approach to merge LV's multi-mission satellite precipitation and evaporation data from various sources and then improves them through a Postprocessing Filtering (PF) scheme to provide coherent datasets of precipitation (p), evaporation (e), water storage changes (Delta s), and discharge (q) that accounts for its water budget closure. Principal component analysis (PCA) is then applied to the merged-improved products to analyze LV's spatio-temporal changes resulting from impacts of climate variation/change. Compared to the original unmerged data (0.62 and 0.37 average correlation for two samples), the merged-improved products are largely in agreement (0.91 average correlation). Furthermore, smaller imbalances between the merged-improved products are obtained with precipitation (37%) and water storage changes (35%) being the largest contributors to LV's water budget. This data improvement scheme could be applicable to any inland lake of a size similar to LV. (C) 2018 Elsevier B.V. All rights reserved.
机译：维多利亚湖（LV）是世界第二大淡水湖，为4,200万人提供了生计，并调节了区域气候。因此，研究由于气候变化/变化和人为因素造成的变化对于其可持续利用至关重要。然而，由于其剪切力的大小，仅依靠稀疏，缺失，不一致或受政府繁文tape节的现场测量来进行此类研究是一项艰巨的任务。遥感产品提供了一种有价值的替代方法，但由于它们源自不同的来源，具有不同的基本假设和模型，因此相互之间大多不一致，因此受到惩罚。这项研究开创了一种程序，该程序使用简单权重方法合并来自不同来源的LV多任务卫星降水和蒸发数据，然后通过后处理滤波（PF）方案对其进行改进，以提供降水（p），蒸发（e）的连贯数据集。 ），储水量变化（Delta s）和排放量（q）来说明其水费预算的关闭情况。然后将主成分分析（PCA）应用于合并后的改进产品，以分析由于气候变化/变化的影响而导致的LV时空变化。与原始的未合并数据相比（两个样本的平均相关性为0.62和0.37），合并后改进后的产品在很大程度上相符（平均相关性为0.91）。此外，合并改良产品之间的失衡较小，降水量（37％）和储水量变化（35％）是LV用水预算的最大贡献者。该数据改进方案可适用于任何大小与LV相似的内陆湖泊。 （C）2018 Elsevier B.V.保留所有权利。

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