The aim of this study is the improvement of the TanDEM-X elevation model for future floodwater modeling by implementing surveyed road dams and the use of filter algorithms. Modern satellite systems like TanDEM-X deliver high-resolution images with a high vertical and horizontal accuracy. Nevertheless, regarding special usage they sometimes reach their limits in documenting important features that are smaller than the grid size. Especially in the context of 2D-hydrodynamic flood modelling, the features that influence the runoff processes, e.g. road dams and culverts, have to be included for precise calculations. To fulfil the objective, the main road dams were surveyed, especially those that are blocking the flood water flowing from south Angola to the Etosha Pan in northern Namibia. First, a Leica GS 16 Sensor was installed on the roof of a car recording position data in real time while driving on the road dams in the Cuvelai Basin. In total, 532 km of road dams have been investigated during 4 days while driving at a top speed of 80 km/h. Due to the long driving distances, the daily regular adjustment of the base station would have been necessary but logistically not possible. Moreover, the lack of reference stations made a RTK and Network-RTK solution likewise impossible. For that reasons, the Leica SmartLink function was used. This method is not dependent on classic reference stations next to the GNSS sensor but instead works with geostationary satellites sending correction data in real time. The surveyed road dam elevation data have a vertical accuracy of 4.3 cm up to 10 cm. These precise measurements contribute to rectifying the TanDEM-X elevation data and thus improve the surface runoff network for the future floodwater model and should enhance the floodwater prediction for the Cuvelai Basin.

中文翻译：

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用于TanDEM-X校正的GNSS移动式道路大坝测量，以改善纳米比亚北部洪水模型的数据库

这项研究的目的是通过实施被调查的公路大坝和使用过滤器算法来改进TanDEM-X高程模型，以用于将来的洪水建模。诸如TanDEM-X之类的现代卫星系统可提供具有高垂直和水平精度的高分辨率图像。但是，对于特殊用途，在记录小于栅格尺寸的重要特征时，有时会达到极限。尤其是在2D流体动力洪水建模的情况下，必须包括影响径流过程的特征（例如公路大坝和涵洞）才能进行精确计算。为了实现这一目标，对主要道路水坝进行了调查，特别是那些阻止洪水从安哥拉南部流向纳米比亚北部埃托沙潘的水坝。第一，在库维莱盆地的公路大坝上行驶时，将Leica GS 16传感器安装在汽车顶棚上，实时记录位置数据。在以最高时速80 km / h行驶的4天中，总共调查了532 km的道路水坝。由于较长的行驶距离，因此有必要对基站进行每日定期调整，但从逻辑上讲不可能。此外，由于缺少参考站，RTK和Network-RTK解决方案同样无法实现。因此，徕卡 此外，由于缺少参考站，RTK和Network-RTK解决方案同样无法实现。因此，徕卡 而且，由于缺少参考站，RTK和Network-RTK解决方案同样无法实现。因此，徕卡使用了SmartLink功能。该方法不依赖于GNSS传感器旁边的经典参考站，而是与对地静止卫星实时发送校正数据一起使用。所调查的公路大坝高程数据的垂直精度为4.3厘米，最高10厘米。这些精确的测量有助于纠正TanDEM-X高程数据，从而改善未来洪水模型的地表径流网络，并应增强Cuvelai盆地的洪水预报。