Estimation of river flow using CubeSats remote sensing

Adriano M Junqueira; Feng Mao; Tatiana S G Mendes; Silvio J C Simões; José A P Balestieri; David M Hannah

doi:10.1016/j.scitotenv.2021.147762

Estimation of river flow using CubeSats remote sensing

Sci Total Environ. 2021 Sep 20:788:147762. doi: 10.1016/j.scitotenv.2021.147762. Epub 2021 May 15.

Authors

Adriano M Junqueira¹, Feng Mao², Tatiana S G Mendes³, Silvio J C Simões⁴, José A P Balestieri⁵, David M Hannah⁶

Affiliations

¹ São Paulo State University (UNESP), School of Engineering, Guaratinguetá, Brazil; University of Birmingham, School of Geography, Earth and Environmental Sciences, Birmingham, United Kingdom. Electronic address: adriano.junqueira@unesp.br.
² Cardiff University, School of Earth and Environmental Sciences, Cardiff, United Kingdom. Electronic address: maof1@cardiff.ac.uk.
³ São Paulo State University (UNESP), Institute of Science and Technology, São José dos Campos, Brazil. Electronic address: tatiana.mendes@ict.unesp.br.
⁴ São Paulo State University (UNESP), Institute of Science and Technology, São José dos Campos, Brazil; University of the Algarve, Centre for Marine and Environmental Research. Electronic address: silvio.simoes@ict.unesp.br.
⁵ São Paulo State University (UNESP), School of Engineering, Guaratinguetá, Brazil. Electronic address: jose.perrella@unesp.br.
⁶ University of Birmingham, School of Geography, Earth and Environmental Sciences, Birmingham, United Kingdom. Electronic address: d.m.hannah@bham.ac.uk.

PMID: 34022571
DOI: 10.1016/j.scitotenv.2021.147762

Abstract

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 (R² = 88.83%) and CS (R² = 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.

Keywords: Cerrado (Savannah); Change detection; CubeSat; Remote sensing; River flow; Spatiotemporal resolution.