River Flow Monitoring by Sentinel-3 OLCI and MODIS: Comparison and Combination
The monitoring of rivers by satellite is an up-to-date subject in hydrological studies as confirmed by the interest of space agencies to finance specific missions that respond to the quantification of surface water flows. We address the problem by using multi-spectral sensors, in the near-infrared (...
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Published in | Remote sensing (Basel, Switzerland) Vol. 12; no. 23; p. 3867 |
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Abstract | The monitoring of rivers by satellite is an up-to-date subject in hydrological studies as confirmed by the interest of space agencies to finance specific missions that respond to the quantification of surface water flows. We address the problem by using multi-spectral sensors, in the near-infrared (NIR) band, correlating the reflectance ratio between a dry and a wet pixel extracted from a time series of images, the C/M ratio, with five river flow-related variables: water level, river discharge, flow area, mean flow velocity and surface width. The innovative aspect of this study is the use of the Ocean and Land Colour Instrument (OLCI) on board Sentinel-3 satellites, compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) used in previous studies. Our results show that the C/M ratio from OLCI and MODIS is more correlated with the mean flow velocity than with other variables. To improve the number of observations, OLCI and MODIS products are combined into multi-mission time series. The integration provides good quality data at around daily resolution, appropriate for the analysis of the Po River investigated in this study. Finally, the combination of only MODIS products outperforms the other configurations with a frequency slightly lower (~1.8 days). |
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AbstractList | The monitoring of rivers by satellite is an up-to-date subject in hydrological studies as confirmed by the interest of space agencies to finance specific missions that respond to the quantification of surface water flows. We address the problem by using multi-spectral sensors, in the near-infrared (NIR) band, correlating the reflectance ratio between a dry and a wet pixel extracted from a time series of images, the C/M ratio, with five river flow-related variables: water level, river discharge, flow area, mean flow velocity and surface width. The innovative aspect of this study is the use of the Ocean and Land Colour Instrument (OLCI) on board Sentinel-3 satellites, compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) used in previous studies. Our results show that the C/M ratio from OLCI and MODIS is more correlated with the mean flow velocity than with other variables. To improve the number of observations, OLCI and MODIS products are combined into multi-mission time series. The integration provides good quality data at around daily resolution, appropriate for the analysis of the Po River investigated in this study. Finally, the combination of only MODIS products outperforms the other configurations with a frequency slightly lower (~1.8 days). |
Author | Iodice, Filippo Restano, Marco Brocca, Luca Tarpanelli, Angelica Benveniste, Jérôme |
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References | Hou (ref_20) 2020; 239 ref_36 Sichangi (ref_12) 2016; 179 ref_35 ref_34 ref_10 ref_31 Calmant (ref_7) 2010; 114 Tarpanelli (ref_19) 2018; 57 ref_39 Tarpanelli (ref_18) 2015; 8 ref_38 Castellarin (ref_27) 2011; 36 ref_37 Scharroo (ref_44) 2016; 12 Palmer (ref_1) 2008; 6 Tarpanelli (ref_13) 2013; 136 Tarpanelli (ref_16) 2017; 195 Schneider (ref_33) 2018; 112 Tarpanelli (ref_30) 2013; 5 Huang (ref_14) 2018; 56 Donlon (ref_25) 2012; 120 Nash (ref_42) 1970; 10 ref_47 Tarpanelli (ref_40) 2017; 108 Kern (ref_45) 2020; 14 ref_46 Zakharova (ref_9) 2019; 568 ref_22 Hirpa (ref_2) 2016; 17 Montanari (ref_28) 2012; 16 Brakenridge (ref_17) 2016; 52 Huang (ref_11) 2018; 219 Li (ref_21) 2019; 55 ref_3 Birkett (ref_6) 2002; 107 Cuevas (ref_41) 2004; 47 Sahoo (ref_23) 2020; 251 ref_26 Claverie (ref_24) 2018; 219 Domeneghetti (ref_29) 2013; 17 Biancamaria (ref_43) 2016; 37 Biancamaria (ref_8) 2017; 59 Brakenridge (ref_15) 2005; 86 Domeneghetti (ref_32) 2014; 149 ref_5 ref_4 |
References_xml | – ident: ref_10 doi: 10.5194/hess-2018-261 – volume: 108 start-page: 249 year: 2017 ident: ref_40 article-title: Exploiting a constellation of satellite soil moisture sensors for accurate rainfall estimation publication-title: Adv. Water Resour. doi: 10.1016/j.advwatres.2017.08.010 – ident: ref_5 – volume: 219 start-page: 115 year: 2018 ident: ref_11 article-title: Discharge estimation in high-mountain regions with improved methods using multisource remote sensing: A case study of the Upper Brahmaputra River publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2018.10.008 – ident: ref_3 – ident: ref_26 – ident: ref_34 – volume: 120 start-page: 37 year: 2012 ident: ref_25 article-title: The global monitoring for environment and security (GMES) sentinel-3 mission publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2011.07.024 – volume: 10 start-page: 282 year: 1970 ident: ref_42 article-title: River flow forecasting through conceptual models, part I: A discussion of principles publication-title: J. Hydrol. doi: 10.1016/0022-1694(70)90255-6 – ident: ref_47 – volume: 59 start-page: 128 year: 2017 ident: ref_8 article-title: Satellite radar altimetry water elevations performance over a 200 m wide river: Evaluation over the Garonne River publication-title: Adv. Space Res. doi: 10.1016/j.asr.2016.10.008 – volume: 8 start-page: 141 year: 2015 ident: ref_18 article-title: Coupling MODIS and Radar Altimetry Data for Discharge Estimation in Poorly Gauged River Basins publication-title: IEEE J. Sel. Top. Appl. – ident: ref_22 doi: 10.3390/rs12172810 – volume: 219 start-page: 145 year: 2018 ident: ref_24 article-title: The Harmonized Landsat and Sentinel-2 surface reflectance data set publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2018.09.002 – ident: ref_39 – volume: 107 start-page: LBA-26-1 year: 2002 ident: ref_6 article-title: Surface water dynamics in the Amazon Basin: Application of satellite radar altimetry publication-title: J. Geophys. Res. Atmos. doi: 10.1029/2001JD000609 – ident: ref_37 – volume: 37 start-page: 307 year: 2016 ident: ref_43 article-title: The SWOT Mission and Its Capabilities for Land Hydrology publication-title: Surv. Geophys. doi: 10.1007/s10712-015-9346-y – volume: 5 start-page: 4145 year: 2013 ident: ref_30 article-title: River discharge estimation by using altimetry data and simplified flood routing modeling publication-title: Remote Sens. doi: 10.3390/rs5094145 – ident: ref_35 – volume: 16 start-page: 3739 year: 2012 ident: ref_28 article-title: Hydrology of the Po River: Looking for changing patterns in river discharge publication-title: Hydrol. Earth Syst. Sci. doi: 10.5194/hess-16-3739-2012 – volume: 17 start-page: 3127 year: 2013 ident: ref_29 article-title: Probabilistic flood hazard mapping: Effects of uncertain boundary conditions publication-title: Hydrol. Earth Syst. Sci. doi: 10.5194/hess-17-3127-2013 – volume: 17 start-page: 1131 year: 2016 ident: ref_2 article-title: The effect of reference climatology on global flood forecasting publication-title: J. Hydrometeorol. doi: 10.1175/JHM-D-15-0044.1 – volume: 86 start-page: 185 year: 2005 ident: ref_15 article-title: Space-based measurement of river runoff publication-title: Eos Trans. AGU doi: 10.1029/2005EO190001 – volume: 14 start-page: 2235 year: 2020 ident: ref_45 article-title: The Copernicus Polar Ice and Snow Topography Altimeter (CRISTAL) high-priority candidate mission publication-title: Cryosphere doi: 10.5194/tc-14-2235-2020 – volume: 112 start-page: 17 year: 2018 ident: ref_33 article-title: Evaluation of multi-mode Cryosat-2 altimetry data over the Po River against in situ data and a hydrodynamic model publication-title: Adv. Water Resour. doi: 10.1016/j.advwatres.2017.11.027 – volume: 47 start-page: 111 year: 2004 ident: ref_41 article-title: An ANOVA test for functional data publication-title: Comput. Stat. Data Anal. doi: 10.1016/j.csda.2003.10.021 – volume: 149 start-page: 130 year: 2014 ident: ref_32 article-title: The use of remote sensing-derived water surface data for hydraulic model calibration publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2014.04.007 – volume: 136 start-page: 47 year: 2013 ident: ref_13 article-title: Toward the estimation of river discharge variations using MODIS data in ungauged basins publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2013.04.010 – ident: ref_46 – volume: 251 start-page: 112092 year: 2020 ident: ref_23 article-title: Copula-based probabilistic spectral algorithms for high-frequent streamflow estimation publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2020.112092 – ident: ref_4 doi: 10.3390/rs12071107 – volume: 52 start-page: 6404 year: 2016 ident: ref_17 article-title: River gauging at global scale using optical and passive microwave remote sensing publication-title: Water Resour. Res. doi: 10.1002/2015WR018545 – volume: 239 start-page: 111629 year: 2020 ident: ref_20 article-title: Global satellite-based river gauging and the influence of river morphology on its application publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2019.111629 – volume: 36 start-page: 299 year: 2011 ident: ref_27 article-title: Identifying robust large-scale flood risk mitigation strategies: A quasi-2D hydraulic model as a tool for the Po river publication-title: Phys. Chem. Earth Parts A/B/C doi: 10.1016/j.pce.2011.02.008 – volume: 114 start-page: 2160 year: 2010 ident: ref_7 article-title: Water levels in the Amazon basin derived from the ERS 2 and ENVISAT radar altimetry missions publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2010.04.020 – volume: 179 start-page: 36 year: 2016 ident: ref_12 article-title: Estimating continental river basin discharges using multiple remote sensing data sets publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2016.03.019 – volume: 56 start-page: 333 year: 2018 ident: ref_14 article-title: Detecting, extracting, and monitoring surface water from space using optical sensors: A review publication-title: Rev. Geophys. doi: 10.1029/2018RG000598 – volume: 55 start-page: 8404 year: 2019 ident: ref_21 article-title: Extending the Ability of Near-Infrared Images to Monitor Small River Discharge on the Northeastern Tibetan Plateau publication-title: Water Resour. Res. doi: 10.1029/2018WR023808 – volume: 195 start-page: 96 year: 2017 ident: ref_16 article-title: Discharge estimation and forecasting by MODIS and altimetry data in Niger-Benue River publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2017.04.015 – ident: ref_38 – ident: ref_31 doi: 10.1002/2015WR017654 – ident: ref_36 – volume: 568 start-page: 322 year: 2019 ident: ref_9 article-title: Use of non-polar orbiting satellite radar altimeters of the Jason series for estimation of river input to the Arctic Ocean publication-title: J. Hydrol. doi: 10.1016/j.jhydrol.2018.10.068 – volume: 12 start-page: 471 year: 2016 ident: ref_44 article-title: Jason continuity of services: Continuing the Jason altimeter data records as Copernicus Sentinel-6 publication-title: Ocean Sci. doi: 10.5194/os-12-471-2016 – volume: 57 start-page: 329 year: 2018 ident: ref_19 article-title: Daily river discharge estimates by merging satellite optical sensors and radar altimetry through artificial neural network publication-title: IEEE Trans. Geosci. Remote doi: 10.1109/TGRS.2018.2854625 – volume: 6 start-page: 81 year: 2008 ident: ref_1 article-title: Climate change and the world’s river basins: Anticipating management options publication-title: Front. Ecol. Environ. doi: 10.1890/060148 |
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SubjectTerms | area color finance flow frequency land moderate resolution imaging spectroradiometer MODIS monitoring multi-mission series Po River reflectance remote sensing river discharge river flow rivers satellites Sentinel-3 OLCI surface water time series analysis velocity width |
Title | River Flow Monitoring by Sentinel-3 OLCI and MODIS: Comparison and Combination |
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