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Assessing the capabilities of the Surface Water and Ocean Topography (SWOT) mission for large lake water surface elevation monitoring under different wind conditions

机译:在不同风能下评估大型湖水表面升高监测的地表水和海洋地形(SWOT)任务的能力

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Lakes are important sources of freshwater and provide essential ecosystem services. Monitoring their spatial and temporal variability, and their functions, is an important task within the development of sustainable water management strategies. The Surface Water and Ocean Topography (SWOT) mission will provide continuous information on the dynamics of continental (rivers, lakes, wetlands and reservoirs) and ocean water bodies. This work aims to contribute to the international effort evaluating the SWOT satellite (2022 launch) performance for water balance assessment over large lakes (e.g., 100?km2). For this purpose, a hydrodynamic model was set up over Mamawi Lake, Canada, and different wind scenarios on lake hydrodynamics were simulated. The derived water surface elevations (WSEs) were compared to synthetic elevations produced by the Jet Propulsion Laboratory (JPL) SWOT high resolution (SWOT-HR) simulator. Moreover, water storages and net flows were retrieved from different possible SWOT orbital configurations and synthetic gauge measurements. In general, a good agreement was found between the WSE simulated from the model and those mimicked by the SWOT-HR simulator. Depending on the wind scenario, errors ranged between approximately ?2 and 5?cm for mean error and from 30 to 70?cm root mean square error. Low spatial coverage of the lake was found to generate important biases in the retrievals of water volume or net flow between two satellite passes in the presence of local heterogeneities in WSE. However, the precision of retrievals was found to increase as spatial coverage increases, becoming more reliable than the retrievals from three synthetic gauges when spatial coverage approaches 100?%, demonstrating the capabilities of the future SWOT mission in monitoring dynamic WSE for large lakes across Canada.
机译:湖泊是淡水的重要来源,提供必要的生态系统服务。监测其空间和时间的可变性及其功能,是可持续水管理策略发展中的重要任务。地表水和海洋地形(SWOT)任务将提供有关大陆(河流,湖泊,湿地和水库)和海洋水体的动态的持续信息。这项工作旨在促进评估SWOT卫星(2022年发射)对大型湖泊的水平评估的绩效的国际努力(例如,100?KM2)。为此目的,建立了一个流体动力学模型,加拿大,加拿大,模拟了湖泊流体动力学的不同风景。将衍生的水表面升高(WSES)与喷射推进实验室(JPL)SWOT高分辨率(SWOT-HR)模拟器产生的合成升高进行比较。此外,从不同可能的SWOT轨道配置和合成计测量中检索水储存和净流量。一般而言,在模型模拟的WSE和由SWOT-HR模拟器模拟的人之间发现了一个良好的一致。根据风情景,误差在约2和5?cm之间的误差,对于平均误差,30到70?cm根均方误差。发现湖泊的低空间覆盖率在WSE中局部异质性存在下,在水体积的检索或净流动中产生重要偏见。然而,由于空间覆盖率增加,检索的精度增加增加,当空间覆盖范围100?%时,从三个合成仪中的检索变得更可靠,展示了未来SWOT任务在加拿大的大湖区监测动态WSE的能力。

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