Published September 2021 | Version v1
Journal article

Estimation of river flow using CubeSats remote sensing

  • 1. University of Birmingham, School of Geography, Earth and Environmental Sciences, Birmingham (United Kingdom)
  • 2. São Paulo State University (UNESP), School of Engineering, Guaratinguetá (Brazil)
  • 3. Cardiff University, School of Earth and Environmental Sciences, Cardiff (United Kingdom)
  • 4. São Paulo State University (UNESP), Institute of Science and Technology, São José dos Campos (Brazil)
  • 5. University of the Algarve, Centre for Marine and Environmental Research (Portugal)

Description

Highlights: • Use of remote sensing data from Planet CubeSats constellation to build and assess a methodology to river flow estimation. • This method has significant opportunity for river flow estimation at ungauged sites at the daily and sub-basin scales. • The improvement of river flow measurements underpins the understanding of changing water cycle and sustainable management. 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.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.scitotenv.2021.147762

Additional details

Identifiers

DOI
10.1016/j.scitotenv.2021.147762;
PII
S0048969721028333;

Publishing Information

Journal Title
Science of the Total Environment
Journal Volume
788
Journal Page Range
vp.
ISSN
0048-9697
CODEN
STENDL

INIS

Country of Publication
Netherlands
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
54059076
Subject category
S54: ENVIRONMENTAL SCIENCES; S47: OTHER INSTRUMENTATION;
Descriptors DEI
FRESH WATER; IMAGE PROCESSING; MONITORS; REMOTE SENSING; SURFACES; WATERSHEDS
Descriptors DEC
HYDROGEN COMPOUNDS; MEASURING INSTRUMENTS; OXYGEN COMPOUNDS; PROCESSING; WATER

Optional Information

Copyright
Copyright (c) 2021 Elsevier B.V. All rights reserved.