Spectral Reflectance in the Spatial-temporal Dynamic of Turbidity, Itaipu Reservoir, Brazil
DOI:
https://doi.org/10.11137/1982-3908_2021_44_41228Keywords:
Suspended solids, NDTI, Landsat-8/OLIAbstract
Water quality and the useful life of reservoirs and dams are influenced by the entry of suspended solids, in addition to reducing their
transparency and storage capacity. It is primary to monitor and analyses its space-time dynamics. Thus, the objective of this work is
to characterize the dynamics of the Itaipu Reservoir waters from turbidity, rainfall and spectral reflectance data. To characterize the
dynamics, the reservoir was divided into 18 aquatic compartments between upstream and downstream, using precipitation data from
the TRMM sensor and Landsat 8 images in different precipitation situations. NDWI, MNDWI and NDTI water spectral indexes were
calculated from Landsat 8 images. The results showed high correlation between the NDTI index and the turbidity (R² = 0.91). Then the
NDTI images were reclassified into low, medium and high turbidity. A strong correlation between turbidity and 4 Band corresponding
to the spectral range of red (R² = 0.94) was also obtained. The precipitation has a determinant influence, being the Paraná River, in the
periods of greater precipitation, the main agent in sediment transport. The space-time dynamics showed that the lateral compartments
of the reservoir have less influence on sediment transport. In this sense, our analysis brought new elements to understand the turbidity
variation in these Itaipu Reservoir compartments, as well as the spectral reflectance dynamics in the space-time characterization related
to turbidity.
References
Abe, C.A., Lobo, F.L., Novo, E.M.L.M, Costa, M. & Dibike, Y. 2019, ‘Modeling the effects of land cover change on sediment concentrations in a gold-mined Amazonian basin’, Regional Environmental Change, vol. 19, no. 6, pp. 1801-13. https://doi.org/10.1007/s10113-019-01513-8
Adams, D.K., Souza, E.P.D. & Costa, A.A. 2009, ‘Moist convection in Amazonia: implications for numerical modelling’, Revista Brasileira de Meteorologia, vol. 24, no. 2, pp.168-78. https://doi.org/10.1590/S0102-77862009000200006
Agostinho, A.A., Ambrósio, A.M., Ferreira, V.S., Oliveira, E.F., Okada, E.K & Suzuki, H.I. 1999, ‘Reservatório de Itaipu: aspectos biológicos e socioeconômicos da pesca’. Relatório Anual (1997/98). UEM-Nupélia e Itaipu Binacional, Maringá.
Allam, M., Khan, M.Y. & Meng, Q. 2020, ‘Retrieval of Turbidity on a Spatio-Temporal Scale Using Landsat 8 SR: A Case Study of the Ramganga River in the Ganges Basin, India’, Applied Sciences, vol. 10, no. 11, p. 3702. https://doi.org/10.3390/app10113702
Almeida, C.T.D., Delgado, R.C., Oliveira Junior, J.F.D., Gois, G. & Cavalcanti, A.S. 2015, ‘Avaliação das estimativas de precipitação do produto 3B43-TRMM do Estado do Amazonas’, Floresta e Ambiente, vol. 22, no. 3, pp. 279-86. https://doi.org/10.1590/2179-8087.112114
Alsdorf, D.E., Rodríguez, E. & Lettenmaier, D.P. 2007, ‘Measuring surface water from space’, Reviews of Geophysics, vol. 45, no. 2. https://doi.org/10.1029/2006RG000197
Agência Nacional das Águas 2021, Região Hidrográfica do Paraná, viewed 15 May 2021, <http://www2.ana.gov.br/Paginas/portais/bacias/parana.aspx>.
Andrade, L.F., Brunkow, R.F., Xavier, C.F., & Domingues, L.L. 1988, ‘Fitoplâncton e características físico-químicas do reservatório de Itaipu (BR)’, Limnologia e manejo de represas. Série Monografias em Limnologia, vol. 1, pp. 205-68.
Barbosa, C.C.F., Novo, E.M.L.M., & Martins, V.S. 2019, ‘Introdução ao Sensoriamento Remoto de Sistemas Aquáticos: princípios e aplicações’, vol. 1. Instituto Nacional de Pesquisas Espaciais.
Baughman, C.A., Jones, B.M., Bartz, K.K., Young, D.B. & Zimmerman, C.E. 2015, ‘Reconstructing turbidity in a glacially influenced lake using the Landsat TM and ETM+ surface reflectance climate data record archive, Lake Clark, Alaska’, Remote Sensing, vol. 7, no. 10, pp. 13692-710. https://doi.org/10.3390/rs71013692
Bid, S. & Siddique, G. 2019, ‘Identification of seasonal variation of water turbidity using NDTI method in Panchet Hill Dam, India’, Modeling Earth Systems and Environment, vol. 5, no. 4, pp. 1179-200. https://doi.org/10.1007/s40808-019-00609-8
Buffon, E.C. 2016, ‘Caracterização limnológica e espectral de dois compartimentos aquáticos do reservatório Itaipu’, Master Dissertation, Universidade Federal de Santa Maria. http://repositorio.ufsm.br/handle/1/9477
Cabral, J.B.P., Wachholz, F., Becegato, V.A. & Nascimento, E.S. 2013, ‘Diagnóstico hidrossedimentológico do reservatório da UHE Caçu-Go’, GeoFocus. Revista Internacional de Ciencia y Tecnología de la Información Geográfica, vol. 13, no. 1, pp. 25-37.
Chalov, S.R., Jarsjö, J., Kasimov, N.S., Romanchenko, A.O., Pietroń, J., Thorslund, J. & Promakhova, E. V. 2015, ‘Spatio-temporal variation of sediment transport in the Selenga River Basin, Mongolia and Russia’, Environmental Earth Sciences, vol. 73, no. 2, pp. 663-80. https://doi.org/10.1007/s12665-014-3106-z
Chelotti, G.B., Martinez, J.M., Roig, H.L. & Olivietti, D. 2019, ‘Space-Temporal analysis of suspended sediment in low concentration reservoir by remote sensing’, Revista Brasileira de Recursos Hídricos, vol. 24. https://doi.org/10.1590/2318-0331.241920180061
Couto, E.V.D., Hayakawa, E.H. & Souza-Filho, E.E.D. 2010, ‘Diagnóstico dos efeitos causados pelas cheias excepcionais de 1982/1983 sobre a planície inundacional do Alto rio Paraná (PR-MS)’, Revista de Geografia, Meio Ambiente e Ensino, vol. 1, no. 1, pp. 83-99.
Danelichen, V.H., Machado, N.G., Biudes, M.S. & Souza, M.C. 2013, ‘TRMM satellite performance in estimated rainfall over the midwest region of Brazil’, Revista Brasileira de Climatologia, vol. 12, no. 1. http://dx.doi.org/10.5380/abclima.v12i1.31203
Davranche, A., Lefebvre, G. & Poulin, B. 2010, ‘Wetland monitoring using classification trees and SPOT-5 seasonal time series’, Remote sensing of environment, vol. 114, no. 3, pp. 552-62. https://doi.org/10.1016/j.rse.2009.10.009
Dogliotti, A.I., Ruddick, K.G., Nechad, B., Doxaran, D. & Knaeps, E. 2015, ‘A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters’, Remote Sensing of Environment, vol. 156, pp. 157-68. https://doi.org/10.1016/j.rse.2014.09.020
Dörnhöfer, K., Klinger, P., Heege, T. & Oppelt, N. 2018, ‘Multi-sensor satellite and in situ monitoring of phytoplankton development in a eutrophic-mesotrophic lake’, Science of The Total Environment, vol. 612, pp. 1200-14. https://doi.org/10.1016/j.scitotenv.2017.08.219
Earth Observation and Environmental Services 2020, ‘Earth Observation and Environmental Services’, viewed, 1 August 2020, <http://www.eomap.com/services/water-quality/>.
EOMAP - see Earth Observation and Environmental Services.
Faye, C., Grippa, M., Kergoat, L. & Robert, E. 2020, ‘Investigating the Drivers of Total Suspended Sediment Regime in the Senegal River Basin Using Landsat 8 Satellite Images’, Journal of Environmental Geography, vol. 13, no. 1-2, pp. 31-42. https://doi.org/10.2478/jengeo-2020-0004
Fondriest Environmental Inc 2014, Turbidity, Total Suspended Solids and Water Clarity, Fundamentals Environmental Measurements. https://www.fondriest.com/environmental-measurements/parameters/water-quality/turbidity-total-suspended-solids-water-clarity/
Galvão, V., Stevaux, J.C. & Saad, A.R. 2014, ‘Análise Geoambiental dos Ambientes da Planície Aluvial do Alto Curso do Rio Paraná: Fragilidade e Impactos Ambientais Relativos ao Desenvolvimento do Uso Turístico’, Geociências, vol. 33, no. 3, pp. 472-91.
Garaba, S.P. & Zielinski, O. 2015, ‘An assessment of water quality monitoring tools in an estuarine system’, Remote Sensing Applications: Society and Environment, vol. 2, pp. 1-10. https://doi.org/10.1016/j.rsase.2015.09.001
Garg, V., Aggarwal, S.P. & Chauhan, P. 2020, ‘Changes in turbidity along Ganga River using Sentinel-2 satellite data during lockdown associated with COVID-19’, Geomatics, Natural Hazards and Risk, vol. 11, no. 1, pp. 1175-95. https://doi.org/10.1080/19475705.2020.1782482
Göransson, G., Larson, M. & Bendz, D. 2013, ‘Variation in turbidity with precipitation and flow in a regulated river system–river Göta Älv, SW Sweden’, Hydrology and Earth System Sciences, vol. 17, no. 7, pp. 2529-42. https://doi.org/10.5194/hess-17-2529-2013
Grimm, A.M. 1988, ‘Verificação de variações climáticas na área do lago de Itaipu’, Anais do Congresso Brasileiro de Meteorologia, Rio de Janeiro.
Güttler, F.N., Niculescu, S. & Gohin, F. 2013, ‘Turbidity retrieval and monitoring of Danube Delta waters using multi-sensor optical remote sensing data: An integrated view from the delta plain lakes to the western–northwestern Black Sea coastal zone’, Remote Sensing of Environment, vol. 132, pp. 86-101. https://doi.org/10.1016/j.rse.2013.01.009
Haibo, Y., Zongmin, W., Hongling, Z., & Yu, G. 2011, ‘Water body extraction methods study based on RS and GIS’, Procedia Environmental Sciences, vol. 10, pp. 2619-24. https://doi.org/10.1016/j.proenv.2011.09.407
Hayakawa, E.H., do Couto, E.V., de Souza Filho, E.E., do Prado, B.R. & Paula, P.F. 2010, ‘Análise temporal da planície de inundação do alto rio Paraná (região de Porto Rico–PR) através de dados de sensoriamento remoto’, Boletim de Geografia, vol. 28, no. 1, pp. 115-26. https://doi.org/10.4025/bolgeogr.v28i1.8086
Heege, T., Kiselev, V., Wettle, M. & Hung, N.N. 2014, ‘Operational multi-sensor monitoring of turbidity for the entire Mekong Delta’, International Journal of Remote Sensing, vol. 35, no. 8, pp. 2910-26. https://doi.org/10.1080/01431161.2014.890300
Heege, T., Schenk, K. & Wilhelm, M.L. 2019, ‘Water Quality Information for Africa from Global Satellite Based Measurements: The Concept Behind the UNESCO World Water Quality Portal’ in A. Froehlich (ed), Space in African Society, Southern Space Studies, Springer, pp. 81-92. https://doi.org/10.1007/978-3-030-06040-4_5
Instituto Agronômico do Paraná 2020, Cartas climáticas do Paraná. Londrina, viewed 20 October 2020, <http://www.iapar.br>.
Itaipu 2020, Itaipu Binacional, viewed 15 October 2020, <http://www.itaipu.gov.br/>.
Junk, W.J., Bayley, P.B. & Sparks, R.E. 1989, ‘The flood pulse concept in river-floodplain systems’, Canadian special publication of fisheries and aquatic sciences, vol. 106, no. 1, pp. 110-27.
Lacaux, J.P., Tourre, Y.M., Vignolles, C., Ndione, J.A. & Lafaye, M. 2007, ‘Classification of ponds from high-spatial resolution remote sensing: Application to Rift Valley Fever epidemics in Senegal’, Remote Sensing of Environment, vol. 106, no. 1, pp. 66-74. https://doi.org/10.1016/j.rse.2006.07.012
Liu, Z. 2015, ‘Comparison of precipitation estimates between Version 7 3-hourly TRMM Multi-Satellite Precipitation Analysis (TMPA) near-real-time and research products’, Atmospheric Research, vol. 153, pp. 119-33. https://doi.org/10.1016/j.atmosres.2014.07.032
Lobo, F.L., Costa, M.P. & Novo, E.M.L.M. 2015, ‘Time-series analysis of Landsat-MSS/TM/OLI images over Amazonian waters impacted by gold mining activities’, Remote Sensing of Environment, vol. 157, pp. 170-84. https://doi.org/10.1016/j.rse.2014.04.030
Longo, M., Camargo, R. & Silva Dias, M.A.F. 2004, ‘Análise das características dinâmicas e sinóticas de um evento de friagem durante a estação chuvosa no sudoeste da Amazônia’, Revista Brasileira de Meteorologia, vol. 19, no. 1, pp. 59-72.
Lu, S., Wu, B., Yan, N. & Wang, H. 2011, ‘Water body mapping method with HJ-1A/B satellite imagery’, International Journal of Applied Earth Observation and Geoinformation, vol. 13, no. 3, pp. 428-434. https://doi.org/10.1016/j.jag.2010.09.006
Ma, M., Wang, X., Veroustraete, F. & Dong, L. 2007, ‘Change in area of Ebinur Lake during the 1998–2005 period’, International Journal of Remote Sensing, vol. 28, no. 24, pp. 5523-5533. https://doi.org/10.1080/01431160601009698
Maliki, A.A., Chabuk, A., Sultan, M.A., Hashim, B.M., Hussain, H.M., & Al-Ansari, N. 2020, ‘Estimation of Total Dissolved Solids in Water Bodies by Spectral Indices Case Study: Shatt al-Arab River’, Water, Air, & Soil Pollution, vol. 231, no. 9, pp. 1-11. https://doi.org/10.1007/s11270-020-04844-z
Martins, V.S., Kaleita, A., Barbosa, C.C., Fassoni-Andrade, A.C., Lobo, F.L. & Novo, E.M.L.M. 2019, ‘Remote sensing of large reservoir in the drought years: Implications on surface water change and turbidity variability of Sobradinho reservoir (Northeast Brazil)’, Remote Sensing Applications: Society and Environment, vol. 13, pp. 275-88. https://doi.org/10.1016/j.rsase.2018.11.006
McFeeters, S.K. 1996, ‘The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features’, International Journal of Remote Sensing, vol. 17, no. 7, pp. 1425-32. https://doi.org/10.1080/01431169608948714
Mi, H., Fagherazzi, S., Qiao, G., Hong, Y. & Fichot, C.G. 2019, ‘Climate change leads to a doubling of turbidity in a rapidly expanding Tibetan lake’, Science of The Total Environment, vol. 688, pp. 952-9. https://doi.org/10.1016/j.scitotenv.2019.06.339
Moraes, B.C., Sodré, G.R.C., Souza, E.B., Ribeiro, J.B.M., Filho, L.G.M., Ferreira, D.B.S. & Oliveira, J.V. 2015, ‘Climatology of Seasonal Rainfall in the Eastern Amazon’, Revista Brasileira de Geografia Física, Recife, vol. 8, no. 5, pp. 1359-73.
NASA - see National Aeronautics and Space Administration.
National Aeronautics and Space Administration 2018, TRMM Instruments, viewed 2 October 2020, <http://trmm.gsfc.nasa.gov/overview_dir/ceres.html>.
Oliveira Junior, J.F.D., Delgado, R.C., Gois, G., Lannes, A., Dias, F.O., Souza, J.C. & Souza, M. 2014, ‘Análise da precipitação e sua relação com sistemas meteorológicos em Seropédica, Rio de Janeiro’, Floresta e Ambiente, vol. 21, no. 2, pp. 140-9. http://dx.doi.org/10.4322/floram.2014.030
Ouillon, S. 2003, ‘An inversion method for reflectance in stratified turbid waters’, International Journal of Remote Sensing, vol. 24, no. 3, pp. 535-58. https://doi.org/10.1080/01431160304986
Ouni, H., Kawachi, A., Irie, M., M’Barek, N.B., Hariga-Tlatli, N. & Tarhouni, J. 2019, ‘Development of water turbidity index (WTI) and seasonal characteristics of total suspended matter (TSM) spatial distribution in Ichkeul Lake, a shallow brackish wetland, Northern-East Tunisia’, Environmental Earth Sciences, vol. 78, no. 6, pp. 1-14. https://doi.org/10.1007/s12665-019-8126-2
Pereira, G., Silva, M.E.S., Moraes, E.C. & Cardozo, F.D.S. 2013, ‘Avaliação dos dados de precipitação estimados pelo satélite TRMM para o Brasil’, Revista Brasileira de Recursos Hídricos, vol. 18, no. 3, pp. 139-148.
Pessi, D.D., Santos, C.S.A.D., Nonato, J.J., Dourado, L.G.A., Silva, O.P., Bassini, R.T., & José, J.V. 2019, ‘Validação das estimativas de precipitação do satélite TRMM no Estado de Mato Grosso, Brasil’, Revista de Ciências Agrárias, vol. 42, no. 1, pp. 81-90. https://doi.org/10.19084/RCA18217
Pinto, C.E., Menezes, P.H., Martinez, J.M., Roig, H.L. & Villar, R.A. 2014, ‘Uso de imagens MODIS no monitoramento do fluxo de sedimentos no reservatório de Três Marias’, Revista Brasileira de Engenharia Agrícola e Ambiental, vol. 18, no. 5, pp. 507-516. https://doi.org/10.1590/S1415-43662014000500007
Potes, M., Costa, M.J., & Salgado, R. 2012, ‘Satellite remote sensing of water turbidity in Alqueva reservoir and implications on lake modelling’, Hydrology and Earth System Sciences, vol. 16, no. 6, pp. 1623-33. https://doi.org/10.5194/hess-16-1623-2012
Quang, N.H., Sasaki, J., Higa, H. & Huan, N.H. 2017, ‘Spatiotemporal variation of turbidity based on landsat 8 oli in cam ranh bay and thuy trieu lagoon, vietnam’, Water, vol. 9, no. 8, p. 570. https://doi.org/10.3390/w9080570
Ribeiro Filho, R.A. 2006, ‘Relações tróficas e limnológicas no reservatório de Itaipu: uma análise do impacto da biomassa pesqueira nas comunidades planctônicas’, PhD Thesis, Universidade de São Paulo.
Ribeiro Filho, R.A. 2008, Evolução histórica das relações tróficas e limnológicas no reservatório de Itaipu: efeitos top-down e bottom-up na produção pesqueira, Relatório final de Pós-Doutorado. UNESP, Rio Claro. https://bv.fapesp.br/pt/bolsas/39226/evolucao-historica-das-relacoes-troficas-e-limnologicas-no-reservatorio-de-itaipu-efeitos-top-down/
Ribeiro Filho, R.A., Petrere Junior, M., Benassi, S.F. & Pereira, J.M.A. 2011, ‘Itaipu Reservoir limnology: eutrophication degree and the horizontal distribution of its limnological variables’, Brazilian Journal of Biology, vol. 71, no. 4, pp. 889-902. https://doi.org/10.1590/S1519-69842011000500010
Ribeiro, L.H.L., Brandimarte, A.L. & Kishi, R.T. 2005, Formation of the Salto Caxias Reservoir (PR)- an approach on the eutrophication process. Acta Limnologica Brasiliensia, vol. 17, no. 2, pp. 155-65.
Robert, E., Grippa, M., Kergoat, L., Pinet, S., Gal, L., Cochonneau, G. & Martinez, J. M. 2016, ‘Monitoring water turbidity and surface suspended sediment concentration of the Bagre Reservoir (Burkina Faso) using MODIS and field reflectance data’, International Journal of Applied Earth Observation and Geoinformation, vol. 52, pp. 243-51. https://doi.org/10.1016/j.jag.2016.06.016
Rocha, A.S.D. & Bade, M.R. 2018, Geografia da bacia hidrográfica do Paraná 3: fragilidades e potencialidades socioambientais, In House, São Paulo.
Saberioon, M., Brom, J., Nedbal, V., Souc̆ek, P. & Císar̆, P. 2020, ‘Chlorophyll-a and total suspended solids retrieval and mapping using Sentinel-2A and machine learning for inland waters’, Ecological Indicators, vol. 113, p. 106236. https://doi.org/10.1016/j.ecolind.2020.106236
Sagan, V., Peterson, K.T., Maimaitijiang, M., Sidike, P., Sloan, J., Greeling, B.A., Maalouf, S. & Adams, C., 2020, ‘Monitoring inland water quality using remote sensing: potential and limitations of spectral indices, bio-optical simulations, machine learning, and cloud computing’, Earth-Science Reviews, p. 103187. https://doi.org/10.1016/j.earscirev.2020.103187
Santos, L.D., Schlindwein, S.L., Fantini, A.C., Henkes, J.A. & Belderrain, M.C.N. 2020, ‘Dinâmica do desmatamento da Mata Atlântica: causas e consequências’, Revista Gestão & Sustentabilidade Ambiental, vol. 9, no. 3, pp. 378-402. http://dx.doi.org/10.19177/rgsa.v9e32020378-402
Secretaria de Estado do Meio Ambiente e Recursos Hídricos Bacias Hidrográficas do Paraná 2013, Série Histórica, Secretaria de Estado do Meio Ambiente e Recursos Hídricos Paraná, 2nd edn, Curitiba.
Serrão, E.A.O., Wanzeler, R.T.S., Santos, C.A., Gonçalves, L.J.M. Lima, A.M.M. & Rocha, E.J.P. 2016, ‘Statistical evaluation between the constellation of precipitation estimates with GPM satellite TRMM: an analysis of the river basin Solimões’, Revista Brasileira de Climatologia, vol. 18, pp. 256-75. http://dx.doi.org/10.5380/abclima.v18i0.43059
Sharma, A., Panigrahy, S., Singh, T.S., Patel, J.G. & Tanwar, H. 2015, ‘Wetland Information system using remote sensing and GIS in Himach Pradesh, India’, Asian Journal of Geoinformatics, vol. 14, no. 4.
Silva, A.P.D.S., Dias, H.C.T., Bastos, R.K.X. & Silva, E. 2009, ‘Qualidade da água do reservatório da Usina Hidrelétrica (UHE) de Peti, Minas Gerais’, Revista Árvore, vol. 33, no. 6, pp. 1063-69. https://doi.org/10.1590/S0100-67622009000600009
Silva, B.L., Montanher, O.C., Novo, E.M.L.M., Barbosa, C.C.F., Maciel, D.A. & Carlos, F.M. 2019, ‘Relação entre o total de sólidos suspensos em corpos hídricos do alto rio paraná e imagens msi/Sentinel-2: estudo preliminar’, XIX Simpósio Brasileiro de Sensoriamento Remoto, INPE, Santos.
Silva, J.S.V., Abdon, M.M. & Rossi, M. 2009, ‘Identificação de padrões de vegetação ciliar em imagens CBERS e respectivo estado de conservação’, Geografia, Rio Claro, vol. 34, pp. 629-41. http://www.alice.cnptia.embrapa.br/alice/handle/doc/663285
Silva, J., Neves, S.D.S. & Basotti, I.S., 2017, ‘Cobertura vegetal e uso da terra na bacia hidrográfica do rio Paraná no Estado de Mato Grosso do Sul, Brasil’, Encuentro de Geografos de América Latina, vol. 16. https://www.embrapa.br/busca-de-publicacoes/-/publicacao/1069074/cobertura-vegetal-e-uso-da-terra-na-bacia-hidrografica-do-rio-parana-no-estado-de-mato-grosso-do-sul-brasil
Singh, S., Bhardwaj, A. & Verma, V.K. 2020, ‘Remote sensing and GIS based analysis of temporal land use/land cover and water quality changes in Harike wetland ecosystem, Punjab, India’, Journal of environmental management, vol. 262, p. 110355. https://doi.org/10.1016/j.jenvman.2020.110355
Somvanshi, S., Kunwar, P., Singh, N.B. & Kachhwaha, T.S. 2011, ‘Water turbidity assessment in part of Gomti River using high resolution Google Earth’s Quickbird satellite data’, In Geospatial World Forum, pp. 18-21.
Souza Filho, E.E. & Fragal, E.H. 2013, ‘A influência do nível fluviométrico sobre as variações de área de água e da cobertura vegetal na planície do alto rio Paraná’, Revista Brasileira de Geomorfologia, vol. 14, no. 1. http://dx.doi.org/10.20502/rbg.v14i1.378
Stevaux, J.C., Martins, D.P. & Meurer, M. 2009, ‘Changes in a large regulated tropical river: The Paraná River downstream from the Porto Primavera Dam, Brazil’, Geomorphology, vol. 113, no. 3-4, pp. 230-38. https://doi.org/10.1016/j.geomorph.2009.03.015
Toniolo, G.R., Gross, J.G., Gaida, W., Facco, D.S., Santos, F.C., Pereira Filho, W. 2019, ‘Estimativa da transparência da água em uma área piloto do reservatório Itaipu por meio de dados do sensor Oli/Landsat-8’, In: XIX Simpósio Brasileiro de Sensoriamento Remoto, INPE, Santos -SP.
Trinh, N.X., Quang, T.T., Ha, P.D., Le Xuan, T., Dinh, C.D., Thanh, T.N., Quang, T.T., Duc, T.D. & Thanh, H.N. 2018, ‘Delimitating inland aqua-ecological zones under different climate conditions in the Mekong Delta region, Vietnam’, Journal of Water and Climate Change, vol. 9, no. 3, pp. 463-79. https://doi.org/10.2166/wcc.2018.181
Vanhellemont, Q. & Ruddick, K. 2014, ‘Turbid wakes associated with offshore wind turbines observed with Landsat 8’, Remote Sensing of Environment, vol. 145, pp. 105-15. https://doi.org/10.1016/j.rse.2014.01.009
Viviano, G., Valsecchi, S., Polesello, S., Capodaglio, A., Tartari, G. & Salerno, F. 2017, ‘Combined use of caffeine and turbidity to evaluate the impact of CSOs on river water quality’, Water, Air, & Soil Pollution, vol. 228, no. 9, pp. 1-11. https://doi.org/10.1007/s11270-017-3505-3
Wachholz, F. 2011, ‘Influência Da Bacia Hidrográfica E Características Espaço-Temporais de Variáveis Limnológicas Sobre Reservatórios No Rio Jacuí - RS’, PhD Thesis, Universidade Estadual Paulista. http://hdl.handle.net/11449/104345
Wachholz, F., Pereira Filho, W. & Sartor, S.C.B. 2011, ‘Influência do uso da terra e precipitação pluviométrica na formação de compartimentos aquáticos no reservatório Rodolfo Costa e Silva-RS, Brasil’, Geografia, vol. 36, no. 3, pp. 551-70.
Wang, G.S., Xia, J., Zhu, Y.Z., Niu, C.W. & Tan, G. 2004, ‘Distributed hydrological modeling based on nonlinear system approach’, Advances in Water Science, vol. 15, no. 4, pp. 521-525.
Wang, H.W., Kondolf, M., Tullos, D. & Kuo, W.C. 2018, ‘Sediment management in Taiwan’s reservoirs and barriers to implementation’, Water, vol. 10, no. 8, pp. 1034. https://doi.org/10.3390/w10081034
Wang, X., Gong, Z. & Pu, R. 2018, ‘Estimation of chlorophyll a content in inland turbidity waters using WorldView-2 imagery: a case study of the Guanting Reservoir, Beijing, China’, Environmental monitoring and assessment, vol. 190, no. 10, pp. 1-16. https://doi.org/10.1007/s10661-018-6978-7
Xu, H. 2006, ‘Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery’, International journal of remote sensing, vol. 27, no 14, pp. 3025-3033. https://doi.org/10.1080/01431160600589179
Yanti, A., Susilo, B. & Wicaksono, P. 2016, ‘The aplication of Landsat 8 OLI for total suspended solid (TSS) mapping in Gajahmungkur reservoir Wonogiri regency 2016’, IOP Conference Series: Earth and Environmental Science, vol. 47, no. 1, p. 012028).
Yu, Y., Zhang, H. & Lemckert, C. 2014, ‘Salinity and turbidity distributions in the Brisbane River estuary, Australia’, Journal of hydrology, vol. 519, pp. 3338-52. https://doi.org/10.1016/j.jhydrol.2014.10.015
Zhang, Q. & Liu, H. 2014, ‘Seasonal changes in physical processes controlling evaporation over inland water’, Journal of Geophysical Research: Atmospheres, vol. 119, no. 16, pp. 9779-92. https://doi.org/10.1002/2014JD021797
Zhang, Y., Zhang, Y., Shi, K., Zha, Y., Zhou, Y. & Liu, M. 2016, ‘A Landsat 8 OLI-based, semianalytical model for estimating the total suspended matter concentration in the slightly turbid Xin’anjiang Reservoir (China)’, IEEE journal of selected topics in applied earth observations and remote sensing, vol. 9, no. 1, pp. 398-413. https://doi.org/10.1109/JSTARS.2015.2509469
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