{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:48:56Z","timestamp":1760240936267,"version":"build-2065373602"},"reference-count":70,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2019,10,24]],"date-time":"2019-10-24T00:00:00Z","timestamp":1571875200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Gravity Recovery and Climate Experiment (GRACE) mission has provided us with unforeseen information on terrestrial water-storage (TWS) variability, contributing to our understanding of global hydrological processes, including hydrological extreme events and anthropogenic impacts on water storage. Attempts to decompose GRACE-based TWS signals into its different water storage layers, i.e., surface water storage (SWS), soil moisture, groundwater and snow, have shown that SWS is a principal component, particularly in the tropics, where major rivers flow over arid regions at high latitudes. Here, we demonstrate that water levels, measured with radar altimeters at a limited number of locations, can be used to reconstruct gridded GRACE-based TWS signals in the Amazon basin, at spatial resolutions ranging from 0.5 to 3\u00b0, with mean absolute errors (MAE) as low as 2.5 cm and correlations as high as 0.98. We show that, at 3\u00b0 spatial resolution, spatially-distributed TWS time series can be precisely reconstructed with as few as 41 water-level time series located within the basin. The proposed approach is competitive when compared to existing TWS estimates derived from physically based and computationally expensive methods. Also, a validation experiment indicates that TWS estimates can be extrapolated to periods beyond that of the model regression with low errors. The approach is robust, based on regression models and interpolation techniques, and offers a new possibility to reproduce spatially and temporally distributed TWS that could be used to fill inter-mission gaps and to extend GRACE-based TWS time series beyond its timespan.<\/jats:p>","DOI":"10.3390\/rs11212487","type":"journal-article","created":{"date-parts":[[2019,10,25]],"date-time":"2019-10-25T04:41:27Z","timestamp":1571978487000},"page":"2487","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Radar Altimetry as a Proxy for Determining Terrestrial Water Storage Variability in Tropical Basins"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0098-5095","authenticated-orcid":false,"given":"Davi de C. D.","family":"Melo","sequence":"first","affiliation":[{"name":"Department of Soils and Rural Engineering, Federal University of Para\u00edba, Areia, PB 58397-000, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9635-7220","authenticated-orcid":false,"given":"Augusto","family":"Getirana","sequence":"additional","affiliation":[{"name":"Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA"},{"name":"Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA"}]}],"member":"1968","published-online":{"date-parts":[[2019,10,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"n\/a","DOI":"10.1029\/2004GL019920","article-title":"The gravity recovery and climate experiment: Mission overview and early results","volume":"31","author":"Tapley","year":"2004","journal-title":"Geophys. Res. Lett."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1038\/s41586-018-0123-1","article-title":"Emerging trends in global freshwater availability","volume":"557","author":"Rodell","year":"2018","journal-title":"Nature"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1175\/JHM-D-15-0096.1","article-title":"Extreme Water Deficit in Brazil Detected from Space","volume":"17","author":"Getirana","year":"2016","journal-title":"J. Hydrometeor."},{"key":"ref_4","first-page":"766","article-title":"Hydrological system time lag responses to meteorological shifts","volume":"21","author":"Melo","year":"2016","journal-title":"Braz. J. Water Resour."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1537","DOI":"10.1002\/2014GL059323","article-title":"A GRACE-based water storage deficit approach for hydrological drought characterization","volume":"41","author":"Thomas","year":"2014","journal-title":"Geophys. Res. Lett."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"999","DOI":"10.1038\/nature08238","article-title":"Satellite-based estimates of groundwater depletion in India","volume":"460","author":"Rodell","year":"2009","journal-title":"Nature"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Famiglietti, J.S., Lo, M., Ho, S.L., Bethune, J., Anderson, K.J., Syed, T.H., Swenson, S.C., de Linage, C.R., and Rodell, M. (2011). Satellites measure recent rates of groundwater depletion in California\u2019s Central Valley. Geophys. Res. Lett., 38.","DOI":"10.1029\/2010GL046442"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"5985","DOI":"10.1002\/2015WR018211","article-title":"Groundwater depletion in Central Mexico: Use of GRACE and InSAR to support water resources management","volume":"52","author":"Castellazzi","year":"2016","journal-title":"Water Resour. Res."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Zhong, Y., Zhong, M., Feng, W., Zhang, Z., Shen, Y., and Wu, D. (2018). Groundwater Depletion in the West Liaohe River Basin, China and Its Implications Revealed by GRACE and In Situ Measurements. Remote Sens., 10.","DOI":"10.3390\/rs10040493"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1951","DOI":"10.1175\/JHM-D-15-0157.1","article-title":"Assimilation of Gridded GRACE Terrestrial Water Storage Estimates in the North American Land Data Assimilation System","volume":"17","author":"Kumar","year":"2016","journal-title":"J. Hydrometeor."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2079","DOI":"10.5194\/hess-19-2079-2015","article-title":"Data assimilation of GRACE terrestrial water storage estimates into a regional hydrological model of the Rhine River basin","volume":"19","author":"Tangdamrongsub","year":"2015","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"10,359","DOI":"10.1002\/2017GL074684","article-title":"Rivers and Floodplains as Key Components of Global Terrestrial Water Storage Variability","volume":"44","author":"Getirana","year":"2017","journal-title":"Geophys. Res. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"044010","DOI":"10.1088\/1748-9326\/7\/4\/044010","article-title":"Surface freshwater storage and dynamics in the Amazon basin during the 2005 exceptional drought","volume":"7","author":"Frappart","year":"2012","journal-title":"Environ. Res. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"11,951","DOI":"10.1002\/2013JD020500","article-title":"Surface freshwater storage and variability in the Amazon basin from multi-satellite observations, 1993\u20132007","volume":"118","author":"Papa","year":"2013","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3290","DOI":"10.1029\/2017WR021674","article-title":"The Total Drainable Water Storage of the Amazon River Basin: A First Estimate Using GRACE","volume":"54","author":"Tourian","year":"2018","journal-title":"Water Resour. Res."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1629","DOI":"10.1016\/j.rse.2010.02.005","article-title":"Interannual variability in water storage over 2003\u20132008 in the Amazon Basin from GRACE space gravimetry, in situ river level and precipitation data","volume":"114","author":"Xavier","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Hirschi, M., Viterbo, P., and Seneviratne, S.I. (2006). Basin-scale water-balance estimates of terrestrial water storage variations from ECMWF operational forecast analysis. Geophys. Res. Lett., 33.","DOI":"10.1029\/2006GL027659"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1007\/s11269-015-1161-1","article-title":"Reconstructed Terrestrial Water Storage Change (\u0394TWS) from 1948 to 2012 over the Amazon Basin with the Latest GRACE and GLDAS Products","volume":"30","author":"Nie","year":"2016","journal-title":"Water Resour. Manag."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"533","DOI":"10.5194\/hess-15-533-2011","article-title":"Past terrestrial water storage (1980\u20132008) in the Amazon Basin reconstructed from GRACE and in situ river gauging data","volume":"15","author":"Becker","year":"2011","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"014002","DOI":"10.1088\/1748-9326\/3\/1\/014002","article-title":"Causes and impacts of the 2005 Amazon drought","volume":"3","author":"Zeng","year":"2008","journal-title":"Environ. Res. Lett"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2300","DOI":"10.1002\/2017GL072564","article-title":"A global reconstruction of climate-driven subdecadal water storage variability","volume":"44","author":"Humphrey","year":"2017","journal-title":"Geophys. Res. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"4107","DOI":"10.1002\/2017GL072994","article-title":"Benefits and Pitfalls of GRACE Data Assimilation: a Case Study of Terrestrial Water Storage Depletion in India","volume":"44","author":"Girotto","year":"2017","journal-title":"Geophys. Res. Lett"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"E1080","DOI":"10.1073\/pnas.1704665115","article-title":"Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data","volume":"115","author":"Scanlon","year":"2018","journal-title":"PNAS"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1223","DOI":"10.1029\/98WR00124","article-title":"Contribution of the TOPEX NASA Radar Altimeter to the global monitoring of large rivers and wetlands","volume":"34","author":"Birkett","year":"1998","journal-title":"Water Resour. Res."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Cazenave, A., and Nerem, R.S. (2004). Present-day sea level change: Observations and causes. Rev. Geophys., 42.","DOI":"10.1029\/2003RG000139"},{"key":"ref_26","unstructured":"Birkett, C.M., Reynolds, C., Beckley, B., and Doorn, B. (2011). Coastal Altimetry, Springer."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1080\/02626660903529023","article-title":"Producing time series of river water height by means of satellite radar altimetry\u2014A comparative study","volume":"55","author":"Roux","year":"2010","journal-title":"Hydrol. Sci. J."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2160","DOI":"10.1016\/j.rse.2010.04.020","article-title":"Water levels in the Amazon basin derived from the ERS 2 and ENVISAT radar altimetry missions","volume":"114","author":"Calmant","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1497","DOI":"10.1016\/j.asr.2011.01.004","article-title":"SOLS: A lake database to monitor in the Near Real Time water level and storage variations from remote sensing data","volume":"47","author":"Jelinski","year":"2011","journal-title":"Adv. Space Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"3530","DOI":"10.1016\/j.rse.2011.08.015","article-title":"Characterization of terrestrial water dynamics in the Congo Basin using GRACE and satellite radar altimetry","volume":"115","author":"Lee","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1696","DOI":"10.1109\/JSTARS.2015.2500599","article-title":"Integrating Landsat Imageries and Digital Elevation Models to Infer Water Level Change in Hoover Dam","volume":"9","author":"Tseng","year":"2016","journal-title":"IEEE J. Select. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"366","DOI":"10.1016\/j.rse.2018.08.030","article-title":"Deriving three dimensional reservoir bathymetry from multi-satellite datasets","volume":"217","author":"Getirana","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"923","DOI":"10.5194\/hess-17-923-2013","article-title":"Estimating water discharge from large radar altimetry datasets","volume":"17","author":"Getirana","year":"2013","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Tarpanelli, A., Brocca, L., Barbetta, S., Lacava, T., Faruolo, M., and Moramarco, T. (2015). Integration of MODIS and Radar Altimetry Data for River Discharge Estimation from Space. Engineering Geology for Society and Territory-Volume 3, Springer.","DOI":"10.1007\/978-3-319-09054-2_121"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1016\/j.jhydrol.2010.04.013","article-title":"Integrating spatial altimetry data into the automatic calibration of hydrological models","volume":"387","author":"Getirana","year":"2010","journal-title":"J. Hydrol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"614","DOI":"10.1002\/wrcr.20077","article-title":"Automatic parameterization of a flow routing scheme driven by radar altimetry data: Evaluation in the Amazon basin","volume":"49","author":"Getirana","year":"2013","journal-title":"Water Resour. Res."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2929","DOI":"10.5194\/hess-17-2929-2013","article-title":"Assimilating in situ and radar altimetry data into a large-scale hydrologic-hydrodynamic model for streamflow forecast in the Amazon","volume":"17","author":"Paiva","year":"2013","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Yamazaki, D., Lee, H., Alsdorf, D.E., Dutra, E., Kim, H., Kanae, S., and Oki, T. (2012). Analysis of the water level dynamics simulated by a global river model: A case study in the Amazon River. Water Resour. Res., 48.","DOI":"10.1029\/2012WR011869"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1007\/s10040-006-0103-7","article-title":"Estimating groundwater storage changes in the Mississippi River basin (USA) using GRACE","volume":"15","author":"Rodell","year":"2007","journal-title":"Hydrogeol. J."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Winter, T.C., Harvey, J.W., Franke, O.L., and Alley, W.M. (1998). Ground Water and Surface Water; A Single Resource, DIANE Publishing Inc.","DOI":"10.3133\/cir1139"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"996","DOI":"10.1002\/hyp.7652","article-title":"New diagnostic estimates of variations in terrestrial water storage based on ERA-Interim data","volume":"25","author":"Mueller","year":"2011","journal-title":"Hydrol. Process."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1179","DOI":"10.1029\/2018WR023333","article-title":"Combining Physically-Based Modeling and Deep Learning for Fusing GRACE Satellite Data: Can We Learn from Mismatch?","volume":"55","author":"Sun","year":"2019","journal-title":"Water Resour. Res."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"3465","DOI":"10.1109\/JSTARS.2017.2684081","article-title":"Automated Generation of Lakes and Reservoirs Water Elevation Changes From Satellite Radar Altimetry","volume":"10","author":"Okeowo","year":"2017","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Schutz, B., Tapley, B., and Born, G.H. (2004). Statistical Orbit Determination, Elsevier.","DOI":"10.1016\/B978-012683630-1\/50020-5"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"2648","DOI":"10.1002\/2014JB011547","article-title":"Improved methods for observing Earth\u2019s time variable mass distribution with GRACE using spherical cap mascons","volume":"120","author":"Watkins","year":"2015","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"9412","DOI":"10.1002\/2016WR019494","article-title":"Global evaluation of new GRACE mascon products for hydrologic applications","volume":"52","author":"Scanlon","year":"2016","journal-title":"Water Resour. Res."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"7547","DOI":"10.1002\/2016JB013007","article-title":"High-resolution CSR GRACE RL05 mascons","volume":"121","author":"Save","year":"2016","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.jog.2012.02.001","article-title":"Analysis of grace uncertainties by hydrological and hydro-meteorological observations","volume":"59\u201360","author":"Riegger","year":"2012","journal-title":"J. Geodyn."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Wahr, J., Swenson, S., and Velicogna, I. (2006). Accuracy of GRACE mass estimates. Geophys. Res. Lett., 33.","DOI":"10.1029\/2005GL025305"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"7490","DOI":"10.1002\/2016WR019344","article-title":"Quantifying and reducing leakage errors in the JPL RL05M GRACE mascon solution","volume":"52","author":"Wiese","year":"2016","journal-title":"Water Resour. Res."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Swenson, S., Wahr, J., and Milly, P.C.D. (2003). Estimated accuracies of regional water storage variations inferred from the Gravity Recovery and Climate Experiment (GRACE). Water Resour. Res., 39.","DOI":"10.1029\/2002WR001808"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1137\/0717021","article-title":"Monotone Piecewise Cubic Interpolation","volume":"17","author":"Fritsch","year":"1980","journal-title":"SIAM J. Numer. Anal."},{"key":"ref_53","first-page":"313","article-title":"Kriging: A method of interpolation for geographical information systems","volume":"4","author":"Oliver","year":"1990","journal-title":"Int. J. Geograph. Inf. Syst."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1007\/s12040-007-0006-6","article-title":"Spatial analyses of groundwater levels using universal kriging","volume":"116","author":"Gundogdu","year":"2007","journal-title":"J. Earth Syst. Sci."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1007\/s10666-008-9174-2","article-title":"Comparison of Groundwater Level Estimation Using Neuro-fuzzy and Ordinary Kriging","volume":"14","author":"Kholghi","year":"2008","journal-title":"Environ. Model Assess"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"2121","DOI":"10.1590\/0001-3765201620150103","article-title":"Geostatistical Approach for Spatial Interpolation of Meteorological Data","volume":"88","author":"Ozturk","year":"2016","journal-title":"Anais Acad. Brasileira Ci\u00eancias"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"991","DOI":"10.1016\/j.envsoft.2005.05.001","article-title":"Evaluation and optimisation of groundwater observation networks using the Kriging methodology","volume":"21","author":"Theodossiou","year":"2006","journal-title":"Environ. Model. Softw."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1016\/j.cageo.2004.03.012","article-title":"Multivariable geostatistics in S: the gstat package","volume":"30","author":"Pebesma","year":"2004","journal-title":"Comput. Geosci."},{"key":"ref_59","unstructured":"Sibson, R. (1981). A Brief Description of Natural Neighbor Interpolation. Interpolating Multivariate Data, John Wiley & Sons."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"3281","DOI":"10.1002\/hyp.7442","article-title":"Improving interpolation of daily precipitation for hydrologic modelling: spatial patterns of preferred interpolators","volume":"23","author":"Kurtzman","year":"2009","journal-title":"Hydro. Process."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/S0022-1694(98)00155-3","article-title":"High-resolution studies of rainfall on Norfolk Island: Part II: Interpolation of rainfall data","volume":"208","author":"Dirks","year":"1998","journal-title":"J. Hydrol."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"04018068","DOI":"10.1061\/(ASCE)HE.1943-5584.0001743","article-title":"Comparison of Interpolation Methods for Spatial Distribution of Monthly Precipitation in the State of Pernambuco, Brazil","volume":"24","author":"Stosic","year":"2019","journal-title":"J. Hydrol. Eng."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1002\/jpln.201600407","article-title":"Surface interpolation of environmental factors as tool for evaluation of the occurrence of high methane and nitrous oxide fluxes","volume":"181","author":"Lengerer","year":"2018","journal-title":"J. Plant Nutr. Soil Sci."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1163","DOI":"10.1016\/j.envsoft.2009.03.009","article-title":"Comparison of interpolation methods for depth to groundwater and its temporal and spatial variations in the Minqin oasis of northwest China","volume":"24","author":"Sun","year":"2009","journal-title":"Environ. Model. Softw."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1016\/j.jhydrol.2016.09.022","article-title":"Spatial interpolation of river channel topography using the shortest temporal distance","volume":"542","author":"Zhang","year":"2016","journal-title":"J. Hydrol."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Niu, G.Y., Yang, Z.L., Mitchell, K.E., Chen, F., Ek, M.B., Barlage, M., Kumar, A., Manning, K., Niyogi, D., and Rosero, E. (2011). The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. J. Geophys. Res. Atmos., 116.","DOI":"10.1029\/2010JD015139"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"1641","DOI":"10.1175\/JHM-D-12-021.1","article-title":"The Hydrological Modeling and Analysis Platform (HyMAP): Evaluation in the Amazon Basin","volume":"13","author":"Getirana","year":"2012","journal-title":"J. Hydrometeor."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"4942","DOI":"10.1002\/2017WR020519","article-title":"Trade-off between cost and accuracy in large-scale surface water dynamic modeling","volume":"53","author":"Getirana","year":"2017","journal-title":"Water Resour. Res."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"3141","DOI":"10.1002\/hyp.7387","article-title":"Sea-tide effects on flows in the lower reaches of the Amazon River","volume":"23","author":"Kosuth","year":"2009","journal-title":"Hydrol. Process."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1175\/BAMS-85-3-381","article-title":"The Global Land Data Assimilation System","volume":"85","author":"Rodell","year":"2004","journal-title":"Bull. Am. Meteorol. Soc."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/21\/2487\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:29:07Z","timestamp":1760189347000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/21\/2487"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10,24]]},"references-count":70,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2019,11]]}},"alternative-id":["rs11212487"],"URL":"https:\/\/doi.org\/10.3390\/rs11212487","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2019,10,24]]}}}