Remote Sensing Section, German Research Centre for Geosciences (GFZ), Potsdam, Germany; Institute of Geographical Sciences, Freie Universität Berlin (FU Berlin), Berlin, Germany.
Remote Sensing Section, German Research Centre for Geosciences (GFZ), Potsdam, Germany.
Sci Total Environ. 2016 Nov 15;571:575-93. doi: 10.1016/j.scitotenv.2016.07.024. Epub 2016 Jul 12.
Water scarcity in the dry season is a vital problem in dryland regions such as northeastern Brazil. Water supplies in these areas often come from numerous reservoirs of various sizes. However, inventory data for these reservoirs is often limited due to the expense and time required for their acquisition via field surveys, particularly in remote areas. Remote sensing techniques provide a valuable alternative to conventional reservoir bathymetric surveys for water resource management. In this study single pass TanDEM-X data acquired in bistatic mode were used to generate digital elevation models (DEMs) in the Madalena catchment, northeastern Brazil. Validation with differential global positioning system (DGPS) data from field measurements indicated an absolute elevation accuracy of approximately 1m for the TanDEM-X derived DEMs (TDX DEMs). The DEMs derived from TanDEM-X data acquired at low water levels show significant advantages over bathymetric maps derived from field survey, particularly with regard to coverage, evenly distributed measurements and replication of reservoir shape. Furthermore, by mapping the dry reservoir bottoms with TanDEM-X data, TDX DEMs are free of emergent and submerged macrophytes, independent of water depth (e.g. >10m), water quality and even weather conditions. Thus, the method is superior to other existing bathymetric mapping approaches, particularly for inland water bodies. The proposed approach relies on (nearly) dry reservoir conditions at times of image acquisition and is thus restricted to areas that show considerable water levels variations. However, comparisons between TDX DEM and the bathymetric map derived from field surveys show that the amount of water retained during the dry phase has only marginal impact on the total water volume derivation from TDX DEM. Overall, DEMs generated from bistatic TanDEM-X data acquired in low water periods constitute a useful and efficient data source for deriving reservoir bathymetry and show great potential in large scale application.
旱季水资源短缺是巴西东北部干旱地区等旱地地区的一个重要问题。这些地区的供水通常来自许多不同大小的水库。然而，由于通过实地调查获取这些水库库存数据的费用和时间，特别是在偏远地区，这些数据通常是有限的。遥感技术为水资源管理提供了一种替代传统水库水深测量的有价值的方法。在这项研究中，使用了双基地模式获取的单通道 TanDEM-X 数据来生成巴西东北部马德拉纳流域的数字高程模型 (DEM)。与实地测量的差分全球定位系统 (DGPS) 数据的验证表明，TanDEM-X 衍生的 DEM（TDX DEM）的绝对高程精度约为 1m。在低水位条件下获取的 TanDEM-X 数据衍生的 DEM 与现场调查衍生的水深图相比具有显著优势，特别是在覆盖范围、均匀分布的测量和水库形状的复现方面。此外，通过使用 TanDEM-X 数据对干涸的水库底部进行测绘，TDX DEM 不受浮出水面和淹没的大型水生植物的影响，与水深（例如>10m）、水质甚至天气条件无关。因此，该方法优于其他现有的水深测绘方法，特别是对于内陆水体。该方法依赖于图像采集时（几乎）干涸的水库条件，因此仅限于水位变化较大的区域。然而，TDX DEM 与实地调查衍生的水深图之间的比较表明，在旱季期间保留的水量对从 TDX DEM 得出的总水量的影响只有很小的影响。总体而言，在低水位期间获取的双基地 TanDEM-X 数据生成的 DEM 是一种有用且高效的水库水深测绘数据源，在大规模应用中具有很大的潜力。
