Sentinel-2 MSI image time series reveal hydrological and geomorphological control of the sedimentation processes in an Amazonian hydropower dam

[1]  B. Rajagopalan,et al.  Estimating Reservoir Sedimentation Rates and Storage Capacity Losses Using High‐Resolution Sentinel‐2 Satellite and Water Level Data , 2023, Geophysical Research Letters.

[2]  D. Muñoz,et al.  Modeling and Analysis of Sediment Trapping Efficiency of Large Dams Using Remote Sensing , 2023, Water Resources Research.

[3]  B. Rajagopalan,et al.  Satellites reveal widespread decline in global lake water storage , 2023, Science.

[4]  Jonathan M. Gomes-Selman,et al.  Reducing adverse impacts of Amazon hydropower expansion , 2022, Science.

[5]  I. Overeem,et al.  Earth’s sediment cycle during the Anthropocene , 2022, Nature Reviews Earth & Environment.

[6]  Sylvain Ferrant,et al.  Sentinel-1&2 Multitemporal Water Surface Detection Accuracies, Evaluated at Regional and Reservoirs Level , 2021, Remote. Sens..

[7]  Jean-Michel Martinez,et al.  Atmospheric and sunglint correction for retrieving chlorophyll-a in a productive tropical estuarine-lagoon system using Sentinel-2 MSI imagery , 2021, ISPRS Journal of Photogrammetry and Remote Sensing.

[8]  P. Nobre,et al.  Avaliação do Balanço de água na Bacia do Rio Madeira Simulado Pelo Modelo Regional Climático Eta e o Modelo Hidrológico de Grandes Bacias MGB , 2021 .

[9]  Maurício C.R. Cordeiro,et al.  Automatic water detection from multidimensional hierarchical clustering for Sentinel-2 images and a comparison with Level 2A processors , 2021 .

[10]  Michael Ondrusek,et al.  Robust algorithm for estimating total suspended solids (TSS) in inland and nearshore coastal waters , 2020, Remote Sensing of Environment.

[11]  Ronald R. Gutierrez,et al.  The potential impact of climate variability on siltation of Andean reservoirs , 2020 .

[12]  F. Roland,et al.  Carbon dioxide emission from drawdown areas of a Brazilian reservoir is linked to surrounding land cover , 2019, Aquatic Sciences.

[13]  Felipe de Lucia Lobo,et al.  Retrieving Total and Inorganic Suspended Sediments in Amazon Floodplain Lakes: A Multisensor Approach , 2019, Remote. Sens..

[14]  Jean-Michel Martinez,et al.  A SEM-based method to determine the mineralogical composition and the particle size distribution of suspended sediment , 2019, International Journal of Sediment Research.

[15]  Jean-Michel Martinez,et al.  Decline of Fine Suspended Sediments in the Madeira River Basin (2003–2017) , 2019, Water.

[16]  Olivier Hagolle,et al.  Validation of Copernicus Sentinel-2 Cloud Masks Obtained from MAJA, Sen2Cor, and FMask Processors Using Reference Cloud Masks Generated with a Supervised Active Learning Procedure , 2019, Remote. Sens..

[17]  Rita de Cássia Condé,et al.  Indirect Assessment of Sedimentation in Hydropower Dams Using MODIS Remote Sensing Images , 2019, Remote. Sens..

[18]  Jean-Michel Martinez,et al.  An index concentration method for suspended load monitoring in large rivers of the Amazonian foreland , 2019, Earth Surface Dynamics.

[19]  E. Moran,et al.  Sustainable hydropower in the 21st century , 2018, Proceedings of the National Academy of Sciences.

[20]  Quinten Vanhellemont,et al.  Atmospheric correction of metre-scale optical satellite data for inland and coastal water applications , 2018, Remote Sensing of Environment.

[21]  K. Falinski,et al.  Loss of Reservoir Capacity through Sedimentation in Hawai‘i: Management Implications for the Twenty-First Century1 , 2018, Pacific Science.

[22]  G. Torrente‐Vilara,et al.  Temporal fish community responses to two cascade run‐of‐river dams in the Madeira River, Amazon basin , 2017 .

[23]  Jean-Michel Martinez,et al.  A reassessment of the suspended sediment load in the Madeira River basin from the Andes of Peru and Bolivia to the Amazon River in Brazil, based on 10 years of data from the HYBAM monitoring programme , 2017 .

[24]  B. Flyvbjerg,et al.  Damming the rivers of the Amazon basin , 2017, Nature.

[25]  Bruno Lartiges,et al.  Variability of apparent and inherent optical properties of sediment-laden waters in large river basins - lessons from in situ measurements and bio-optical modeling. , 2017, Optics express.

[26]  V. Martinez,et al.  The political ecology of hydropower: Social justice and conflict in Colombian hydroelectricity development , 2016 .

[27]  Jianhua Zhu,et al.  Development of a Semi-Analytical Algorithm for the Retrieval of Suspended Particulate Matter from Remote Sensing over Clear to Very Turbid Waters , 2016, Remote. Sens..

[28]  Chenghai Wang,et al.  Projected 21st century changes in snow water equivalent over Northern Hemisphere landmasses from the CMIP5 model ensemble , 2015 .

[29]  Raul Espinoza-Villar,et al.  The optical properties of river and floodplain waters in the Amazon River Basin: Implications for satellite‐based measurements of suspended particulate matter , 2015 .

[30]  P. Warren,et al.  The impacts of ‘run‐of‐river’ hydropower on the physical and ecological condition of rivers , 2015 .

[31]  Carol J. Miller,et al.  Sediment accumulation rates and sediment dynamics using five different methods in a well-constrained impoundment: Case study from Union Lake, Michigan , 2015 .

[32]  Martin W. Doyle,et al.  Reservoir Sedimentation and Storage Capacity in the United States: Management Needs for the 21st Century , 2015 .

[33]  J. Grimalt,et al.  Massive accumulation of highly polluted sedimentary deposits by river damming. , 2014, The Science of the total environment.

[34]  Zhongfeng Qiu,et al.  A simple optical model to estimate suspended particulate matter in Yellow River Estuary. , 2013, Optics express.

[35]  J. Moquet,et al.  Climatic control on eastern Andean denudation rates (Central Cordillera from Ecuador to Bolivia) , 2013 .

[36]  Jean-Michel Martinez,et al.  A study of sediment transport in the Madeira River, Brazil, using MODIS remote-sensing images , 2013 .

[37]  Philippe Vauchel,et al.  The integration of field measurements and satellite observations to determine river solid loads in poorly monitored basins , 2012 .

[38]  Harry H. Roberts,et al.  The Mississippi Delta Region: Past, Present, and Future , 2012 .

[39]  B. Nechad,et al.  Calibration and validation of a generic multisensor algorithm for mapping of total suspended matter in turbid waters , 2010 .

[40]  S. Dadson,et al.  The partitioning of the total sediment load of a river into suspended load and bedload: a review of empirical data , 2009 .

[41]  C. Revenga,et al.  Fragmentation and Flow Regulation of the World's Large River Systems , 2005, Science.

[42]  C. Vörösmarty,et al.  Anthropogenic sediment retention: major global impact from registered river impoundments , 2003 .

[43]  N. Poff,et al.  How Dams Vary and Why It Matters for the Emerging Science of Dam Removal , 2002 .

[44]  D. Doxaran,et al.  Spectral signature of highly turbid waters: Application with SPOT data to quantify suspended particulate matter concentrations , 2002 .

[45]  C. Mobley,et al.  Estimation of the remote-sensing reflectance from above-surface measurements. , 1999, Applied optics.

[46]  P. Sen.  Estimates of the Regression Coefficient Based on Kendall's Tau , 1968 .

[47]  G. Brune.  Trap efficiency of reservoirs , 1953 .

[48]  H. B. Mann.  Nonparametric Tests Against Trend , 1945 .

[49]  J. Sedlacek,et al.  Reservoir deltas and their role in pollutant distribution in valley-type dam reservoirs: Les Království Dam, Elbe River, Czech Republic , 2020 .

[50]  T. Harmel,et al.  Sunglint correction of the Multi-Spectral Instrument (MSI)-SENTINEL-2 imagery over inland and sea waters from SWIR bands , 2018 .