São Paulo State University (UNESP), School of Engineering, Guaratinguetá, Brazil; University of Birmingham, School of Geography, Earth and Environmental Sciences, Birmingham, United Kingdom.
Cardiff University, School of Earth and Environmental Sciences, Cardiff, United Kingdom.
Sci Total Environ. 2021 Sep 20;788:147762. doi: 10.1016/j.scitotenv.2021.147762. Epub 2021 May 15.
River flow characterizes the integrated response from watersheds, so it is essential to quantify to understand the changing water cycle and underpin the sustainable management of freshwaters. However, river gauging stations are in decline with ground-based observation networks shrinking. This study proposes a novel approach of estimating river flows using the Planet CubeSats constellation with the possibility to monitor on a daily basis at the sub-catchment scale through remote sensing. The methodology relates the river discharge to the water area that is extracted from the satellite image analysis. As a testbed, a series of Surface Reflectance PlanetScope images and observed streamflow data in Araguaia River (Brazil) were selected to develop and validate the methodology. The study involved the following steps: (1) survey of measurements of water level and river discharge using in-situ data from gauge-based Conventional Station (CS) and measurements of altimetry using remote data from JASON-2 Virtual Station (JVS); (2) survey of Planet CubeSat images for dates in step 1 and without cloud cover; (3) image preparation including clipping based on different buffer areas and calculation of the Normalized Difference Vegetation Index (NDVI) per image; (4) water bodies areas calculation inside buffers in the Planet CubeSat images; and (5) correlation analysis of CubeSat water bodies areas with JVS and CS data. Significant correlations between the water bodies areas with JVS (R = 88.83%) and CS (R = 96.49%) were found, indicating that CubeSat images can be used as a CubeSat Virtual Station (CVS) to estimate the river flow. This newly proposed methodology using CubeSats allows for more accurate results than the JVS-based method used by the Brazilian National Water Agency (ANA) at present. Moreover, CVS requires small areas of remote sensing data to estimate with high accuracy the river flow and the height variation of the water in different timeframes. This method can be used to monitor sub-basin scale discharge and to improve water management, particularly in developing countries where the presence of conventional stations is often very limited.
河流流量是流域综合响应的特征，因此量化河流流量对于理解不断变化的水循环和支持淡水的可持续管理至关重要。然而，随着地面观测网络的缩小，河流量测站正在减少。本研究提出了一种使用 Planet CubeSat 卫星星座估算河流流量的新方法，有可能通过遥感每天在子流域尺度上进行监测。该方法将河流流量与从卫星图像分析中提取的水域面积相关联。作为一个试验台，选择了一系列 Araguaia 河（巴西）的地表反射 PlanetScope 图像和观测到的流量数据，以开发和验证该方法。该研究包括以下步骤：（1）使用常规站（CS）的现场数据和 Jason-2 虚拟站（JVS）的远程数据测量水位和河流流量；（2）在步骤 1 中调查 CubeSat 图像日期，并且没有云覆盖；（3）图像准备包括基于不同缓冲区的裁剪和每个图像的归一化差异植被指数（NDVI）的计算；（4）在 Planet CubeSat 图像的缓冲区中计算水体区域；（5）CubeSat 水体区域与 JVS 和 CS 数据的相关分析。发现 CubeSat 水体区域与 JVS（R=88.83%）和 CS（R=96.49%）之间存在显著相关性，表明 CubeSat 图像可用于作为 CubeSat 虚拟站（CVS）来估算河流流量。与巴西国家水务局（ANA）目前使用的基于 JVS 的方法相比，这种新提出的使用 CubeSats 的方法可以提供更准确的结果。此外，CVS 需要小面积的遥感数据，以便在不同时间框架内以高精度估算河流流量和水位变化。该方法可用于监测子流域尺度的流量，改善水资源管理，特别是在常规站往往非常有限的发展中国家。
